The Highly Flattened Dark Matter Halo of NGC 4244

In a previous paper (Olling 1995, \aj, 110, 591; astro-ph/9505002) a method was developed to determine the shapes of dark matter halos of spiral galaxies from an accurate determination of the rotation curve, the flaring of the gas layer and the velocity dispersion in the HI. Here this method is applied to the almost edge-on Scd galaxy NGC 4244 for which the necessary parameters are determined in the accompanying paper (AJ, Aug. 1996; astro-ph/9605110). The observed flaring of the HI beyond the optical disk puts significant constraints on the shape of the dark matter halo, which are almost independent of the stellar mass-to-light ratio. NGC 4244's dark matter halo is found to be highly flattened with a shortest-to-longest axis ratio of 0.2 (-0.1)(+0.3). If the dark matter is disk-like, the data presented in this paper imply that the vertical velocity dispersion of the dark matter must be 10% - 30% larger than the measured tangential dispersion in the HI. Alternatively, the measured flaring curve is consistent with a round halo if the gaseous velocity dispersion ellipsoid is anisotropic. In that case the vertical dispersion of the gas is 50 - 70% of the measured tangential velocity dispersion.Comment: 16 pages LaTeX, uses aaspptwo style (357kByte). Includes 3 figures. Complete paper, is also available at http://www.astro.soton.ac.uk/~olling/PrePrints/Paper_03/ or via anonymous ftp at ftp.astro.soton.ac.uk, cd pub/olling/Paper_03 To be published in the Aug. 1996 issue of the Astronomical Journa

Detecting and predicting spatial and interannual patterns of temperate forest springtime phenology in the eastern U.S.

We performed a diagnostic analysis of AVHRR-NDVI and gridded, temperature data for the deciduous forests of the eastern U.S., calibrating temperature accumulation model with satellite data for 1982–1993. The model predicts interannual variability in onset date based upon year-to-year changes in springtime temperature. RMS error over the period ranges from 6.9 days in the northern portion of the domain to 10.7 days in the south. The analysis revealed a relationship between temperature accumulation and satellite derived onset date (rank correlation = 0.31–0.62). The required temperature accumulation threshold can be expressed as a function of mean temperature (R2 of 0.90) to facilitate predictive analysis of phenological onset, or when remote sensing data are unavailable

Trends in wintertime climate in the northeastern United States: 1965–2005

Humans experience climate variability and climate change primarily through changes in weather at local and regional scales. One of the most effective means to track these changes is through detailed analysis of meteorological data. In this work, monthly and seasonal trends in recent winter climate of the northeastern United States (NE-US) are documented. Snow cover and snowfall are important components of the region\u27s hydrological systems, ecosystems, infrastructure, travel safety, and winter tourism and recreation. Temperature, snowfall, and snow depth data were collected from the merged United States Historical Climate Network (USHCN) and National Climatic Data Center Cooperative Network (COOP) data set for the months of December through March, 1965–2005. Monthly and seasonal time series of snow-covered days (snow depth \u3e2.54 cm) are constructed from daily snow depth data. Spatial coherence analysis is used to address data quality issues with daily snowfall and snow depth data, and to remove stations with nonclimatic influences from the regional analysis. Monthly and seasonal trends in mean, minimum, and maximum temperature, total snowfall, and snow-covered days are evaluated over the period 1965–2005, a period during which global temperature records and regional indicators exhibit a shift to warmer climate conditions. NE-US regional winter mean, minimum, and maximum temperatures are all increasing at a rate ranging from 0.42° to 0.46°C/decade with the greatest warming in all three variables occurring in the coldest months of winter (January and February). The regional average reduction in number of snow-covered days in winter (−8.9 d/decade) is also greatest during the months of January and February. Further analysis with additional regional climate modeling is required to better investigate the causal link between the increases in temperature and reduction in snow cover during the coldest winter months of January and February. In addition, regionally averaged winter snowfall has decreased by about 4.6 cm/decade, with the greatest decreases in snowfall occurring in December and February. These results have important implications for the impacts of regional climate change on the northeastern United States hydrology, natural ecosystems, and economy