查看更多>>摘要：The effects of interannual climate variability on water demand in Albuquerque, New Mexico, are assessed. This city provides an ideal setting for examining the effects of climate on urban water demand, because at present the municipal water supply is derived entirely from groundwater, making supply insensitive to short-term climate variability. There is little correlation between interannual variability of climate and total water demand-a result that is consistent with several previous studies. However, summertime residential demand, which composes about one-quarter of total annual demand in Albuquerque, is significantly correlated with summer-season precipitation and average daily maximum temperature. Furthermore, regressions derived from year-to-year changes in these variables are shown to isolate the climatic modulation of residential water demand effectively. Over 60% of the variance of year-to-year changes in summer residential demand is accounted for by interannual temperature and precipitation changes when using a straightforward linear regression model, with precipitation being the primary correlate. Long-term trends in water demand follow population growth closely until 1994, after which time a major water conservation effort led to absolute decreases in demand in subsequent years. The effectiveness of the conservation efforts can be quantified by applying the regression model, thus removing the year-to-year variations associated with short-term climate fluctuations estimated from the preconservation period. The preconservation regression provides a good fit to interannual summer residential demand in subsequent years, demonstrating that the regression model has successfully isolated the climatic component of water demand. The quality of this fit during a period of sharply reduced demand suggests that the conservation program has effectively targeted the nonclimatically sensitive component of water demand and has sharpened the climatically sensitive component of demand to a level closer to the consumption that is 'climatically needed.'
查看更多>>摘要：The city of Houston, Texas, is near a complex coastline and numerous petrochemical plants, the combination of which plays a large role in Houston's air pollution events. It has long been known that the thermally driven afternoon onshore flow (sea breeze or gulf breeze) transports ozone-rich air inland. As a way of quantifying the role of the gulf breeze in Houston's high-ozone events, cluster analysis of hourly averaged surface winds from a regional network of meteorological sensors was performed for 27 summer days of 2000, with the dates coinciding with the Texas Air Quality Study 2000 (TexAQS 2000). Hourly averaged winds were partitioned into 16 independent clusters, or wind patterns, while simultaneously keeping track of the maximum ozone in the network for each hour. Clusters emerged that represented various wind patterns, including thermally driven flows, stagnant winds, and a thunderstorm outflow. All clusters were used to assess which wind patterns were most likely to be coincident with the maximum ozone of the day. High ozone was most likely to occur with clusters representing the gulf breeze. Clusters occurring before the ozone maximum of the day were analyzed to determine which sequences of wind patterns were most likely to precede high ozone. A transition from offshore flow to onshore flow, with at least 1 h of stagnant winds in between, routinely occurred in the 6 h preceding ozone measurements reaching greater than or equal to 120 parts per billion by volume (ppbv). On nontransition days with high ozone, ozone maxima greater than or equal to 120 ppbv often occurred the hour after a wind direction shift of greater than about 45 degree .
查看更多>>摘要：Modeling the increase in the central pressure of tropical cyclones following landfall plays a critical role in the estimation of the hurricane wind hazard at locations removed from the coastline. This paper describes the development of simple empirical models for estimating the rate at which tropical cyclones decay after making landfall. For storms making landfall along the Gulf of Mexico Coast and the coast of the Florida Peninsula, it is shown that the rate of storm filling is proportional to the central pressure difference and translation speed at the time of landfall and is inversely proportional to the radius to maximum winds. Along the Atlantic Coast the effect of radius to maximum winds does not play as significant a role in the rate of storm decay as compared with that seen in Florida and along the Gulf Coast. The models developed here can readily be included in any hurricane simulation model designed for estimating wind speeds in the United States.
查看更多>>摘要：Determination of the scale of the interaction between precipitation and topography is important for the accurate interpolation of rainfall in mountainous areas and also provides insight into the physical processes involved. In this paper, trivariate thin-plate smoothing splines are used to investigate the scale of interaction between monthly precipitation and topography by interpolating monthly rainfall over three subregions of the Australian continent, incorporating different climatic conditions and rainfall types. The interpolations are based upon elevations derived from digital elevation models (DEMs) of various resolutions. All of the DEMs are local averages of version 2.0 of the 9-s-resolution DEM of Australia. The results suggest that the optimal scale of the interaction between precipitation and topography, as it pertains to the elevation-dependent interpolation of monthly precipitation in Australia, is between 5 and 10 km. This is in agreement with results of similar studies that addressed daily precipitation over Switzerland.
查看更多>>摘要：An understanding of the vertical structure of clouds is important for remote sensing of precipitation from space and for the parameterization of cloud microphysics in numerical weather prediction (NWP) models. The representation of cloud hydrometeor profiles in high-resolution NWP models has direct applications in inversion-type precipitation retrieval algorithms [e.g., the Goddard profiling (GPROF) algorithm used for retrieval of precipitation from passive microwave sensors] and in quantitative precipitation forecasting. This study seeks to understand how the vertical structure of hydrometeors (liquid and frozen water droplets in a cloud) produced by high-resolution NWP models with explicit microphysics, henceforth referred to as cloud-resolving models (CRMs), compares to observations. Although direct observations of 3D hydrometeor fields are not available, comparisons of modeled and observed radar echoes can provide some insight into the vertical structure of hydrometeors and, in turn, into the ability of CRMs to produce precipitation structures that are consistent with observations. Significant differences are revealed between the vertical structure of observed and modeled clouds of a severe midlatitude storm over Texas for which the surface precipitation is reasonably well captured. Possible reasons for this discrepancy are presented, and the need for future research is highlighted.
NSTL