Showing papers on "Weather station published in 1999"

Representativeness of local snow data for large scale hydrologic investigations

Abstract: Arctic snow cover usually attains maximum values at the end of winter and such information is important for hydrological investigations because most floods are associated with spring snowmelt. Snow data from weather stations or collected at some local sites are often extrapolated to large areas, but without verifying that the upscaling procedure yields correct results. This study compares maximum snow cover data gathered over two large target areas (170 to 300 km 2 ) with weather station snow course measurements to determine the representativeness of local-scale data for areas typically occupied by large grid cells of macro-hydrological models, The field snow survey results confirmed the controlling role of terrain on snow distribution in the High Arctic. The variability of areal mean snow water equivalence for a grid cell (with dimensions of 1 × 1 km 2 to 13 × 13 km 2 ) increases with terrain complexity but decreases with grid size. Although point data do not represent the snow cover over an area, an attempt was made to upscale the weather station data to the target areas using an index method. Test results show that this index approach works well in the area with a shallow snow cover, but the error increases for an area with relatively deep snow. More effort is needed to refine this method, perhaps in conjunction with remote sensing, so that point data can be upscaled to yield snow information suitable for large-scale hydrological models or land surface schemes.

Establishing more truth in true winds

Abstract: Techniques are presented for the computation and quality control of true winds from vessels at sea. Correct computation of true winds and quality-control methods are demonstrated for complete data. Additional methods are presented for estimating true winds from incomplete data. Recommendations are made for both existing data and future applications. Quality control of automated weather station (AWS) data at the World Ocean Circulation Experiment Surface Meteorological Data Center reveals that only 20% of studied vessels report all parameters necessary to compute a true wind. Required parameters include the ship’s heading, course over the ground (COG), speed over the ground, wind vane zero reference, and wind speed and direction relative to the vessel. If any parameter is omitted or incorrect averaging is applied, AWS true wind data display systematic errors. Quantitative examples of several problems are shown in comparisons between collocated winds from research vessels and the NASA scatterometer...

A New Beaufort Equivalent Scale

Abstract: By comparing Beaufort estimates with simultaneous wind speed measurements the relationship between both parameters can be determined in form of a Beaufort equivalent scale. Previous equivalent scales were derived without regard to the fact, that the error variances of the basic observations are different. In most cases, the variance of only one parameter minimized, either the variance of the Beaufort estimated or the variance of wind measurements. Such regression methods do not yield the universal relationship between both parameters, which is required for an equivalent scale. Therefore a new Beaufort equivalent scale is derived by comparing the three-hourly wind speed measurements from six North Atlantic Ocean weather stations between 1960 and 1971 with more than 300,000 Beaufort estimates of passing merchant ships. But these two raw data sets are not comparable without regard to the different structure of error variances. Firstly the random observation errors of the estimates and of the measurements are calculated to separate the error variance from natural wind variability in both data sets. In this way it can be shown that, as expected, the measurements from ocean weather stations are much more accurate than wind estimates. The difference in accuracy can be quantified. Secondly, daily means of wind speed from the measurements of the stationary ocean weather ships and spatial means from simultaneous estimates of surrounding merchant ships within an averaging area are computed. The latter comprise more individual observations than the means of ocean weather ships, so that the effects of the different observation accuracies are compensated. The radius of averaging areas are calculated separately for each season and each region, so that the spatial variability within this area is equal to the temporal variability at the ocean weather station within 24 hours. Only such pairs of averaged observations are suitable, because neither random observation errors nor natural variability has a falsifying effect. On these especially generated data pairs the method of cumulative frequencies, which allows one to detect also non-linear relationships, is applied in order to obtain the optimal Beaufort equivalent scale.

A Rare Long Record of Deep Soil Temperatures Defines Temporal Temperature Changes and an Urban Heat Island

Abstract: A long-term set of deep soil temperature data collected over a 64-year period beginning in 1889 in a rural Illinois area provide a rare opportunity to assess the natural shifts in temperatures in a pristine environment without any urban or instrument bias. Temperatures from 1901 to 1951 increased 0.4 °C, and this was 0.2 °C less than nearby values from two high quality surface temperature data sets that supposedly are without any influence of urban heat islands, shifts in station locations or instrumentation, or other changes with time. Comparison of the soil values with surface air temperatures from a nearby weather station in a growing university community revealed a heat island effect of 0.6 °C. This value is larger than the adjustment based on population that has been recommended to eliminate the urban bias in long-term temperature trends in the U.S. Collectively, the results suggest that additional efforts may be needed to eliminate the urban influence on air temperatures, beyond techniques that simply use population as the basis. Population is only an approximation of urban factors affecting surface temperatures, and the heat island influences inherent in the values from weather stations in smaller communities which have been used as control, or data assumed to be unaffected by their urban environment in the adjustment procedures, have not been adequately accounted for.

A statistical modeling approach for the simulation of local paleoclimatic proxy records using general circulation model output

Abstract: A statistical modeling approach is proposed for the simulation of local paleoclimatic proxy records using general circulation model (GCM) output. A method for model-consistent statistical downscaling to local weather conditions is developed which can be used as input for process-based proxy models in order to investigate to what extent climate variability obtained from proxy data can be represented by a GCM, and whether, for example, the response of glaciers to climatic change can be reproduced. Downscaling is based on a multiple linear forward regression model using daily sets of operational weather station data and large-scale predictors at various pressure levels obtained from reanalyses of the European Centre for Medium-Range Weather Forecasts. Composition and relative impact of predictors vary significantly for individual stations within the area of investigation. Owing to a strong dependence on individual synoptic-scale patterns, daily data give the highest performance which can be further increased by developing seasonal-specific relationships. The model is applied to a long integration of a GCM coupled to a mixed layer ocean (ECHAM4/MLO) simulating present-day and preindustrial climate variability. Patterns of variability are realistically simulated compared to observed station data within an area of Norway for the period 1868–1993.

Portable meteorological information system

Abstract: A meteorological information system useable by aircraft pilots and others. A receiver-calculator unit receives raw meteorological data and site-specific physical data from a ground-based weather station having a signal transmitter for broadcasting signals conveying data about weather conditions at the station. The transmitted raw data signals are received by the receiver-calculator unit in the aircraft. The receiver-calculator unit may feature an input with which the operator inputs information about the physical character, such as the heading, of the runway of interest. The receiver-calculator unit processes both received raw weather data and received site-specific physical data, and/or operator-input data, to derive additional meteorological information. The raw and derived weather conditions information is displayed by the unit to be available to the aircraft pilot during landing or take-off maneuvers. Optionally, the apparatus uses known algorithms for determining aircraft performance characteristics to process raw and derived weather and site-specific data to determine the relative safety of proposed aircraft maneuvers, such as take-off.

Representativeness of arctic weather station data for the computation of snowmelt in a small area

Abstract: This study determines how representative the snowmelt values computed using arctic weather station data are of the melt in its surrounding area. Simultaneous measurements of meteorological variables were made at several sites to permit comparisons of their calculated snowmelt with the weather station at Resolute. Northwest Territories, Canada. Like most other stations, the Resolute site is located near the coast, at an airport and close to human settlement, making it warmer and its snow albedo lower than its adjacent sites. Snowmelt rates at Resolute are higher than that of a flat site away from the airport, This latter site has snowmelt conditions more typical of the rolling terrain nearby, but its melt rates are higher than those for an inland site where the snow remains longer than at the coastal zone, Through these simultaneous observations and systematic comparisons, this study indicates that the point data from coastal, arctic stations are unlikely to be representative of their surrounding areas. Thus, caution should be exercised when applying such information directly to the computation of snowmelt for entire grid cells of macro-hydrologic models.

Estimating the Value of Precipitation Forecast Information in Alfalfa Dry Hay Production in Ontario

Abstract: The value of weather forecast information to farmers is an important component of program evaluation of weather information systems. No empirical studies have attempted to provide this kind of information for Canadian producers. In this study, a farm level production economics model was used to characterize the value of precipitation forecast information to alfalfa (Medicago sativa L) dry hay producers in the province of Ontario. This model was applied to precipitation forecast data from the Windsor and the London Environment Canada weather offices for the crop years of 1994 and 1995. Four forecast methods are compared. Precipitation damage relationships during harvest are estimated using an agronomic simulation model combined with expert opinion. The value of weather forecast information was found to vary considerably between 1994 and 1995. For the region served by the London Ontario weather station, our results indicate that the Environment Canada daily precipitation forecast was worth $30.23 (Cdn)/acre in 1994 and $26.39 (Cdn)/acre in 1995. For the region served by the Waterloo weather station, the 1994 forecast was worth $36.08/acre. In contrast, producers who followed the 1995 forecast would have been worse off by $5.72 (Cdn)/acre relative to what they would have been able to earn by naively assuming that precipitation over the next 4 d would be the same as the last 4 d. The level of risk aversion of the producer was not found to be an important determinant of the value of weather forecast Information. Averages of the range of values of weather forecast information obtained in this study Indicate that precipitation forecast information is of considerable value to producers at critical times in the production process for alfalfa dry hay.

***WITHDRAWN PATENT AS PER THE LATEST USPTO WITHDRAWN LIST***Severe weather detector and alarm

Abstract: A compact, portable weather station for predicting local extreme weather conditions and for reporting remote weather conditions. The weather station has sensors for determining local temperature, barometric pressure, humidity, ambient light, and ambient static charge. A microprocessor has memory for storing data relating to past weather conditions and data processing apparatus and algorithms for determining probable developing weather conditions responsive to sensed local conditions. The weather station has a radio receiver for communicating with global weather reporting communications systems utilizing cellular communications. Operating commands, predicted local weather conditions, and remote weather conditions are annunciated in synthesized voice in any one of a variety of predetermined languages. The weather station includes voice synthesizing and recognition apparatus for annunciating verbal prompts and weather conditions, and for responding to vocal control. The weather station is formed in two separable components, one having sensors and the other having radio communications apparatus. The microprocessor is preferably contained within the component having radio communications apparatus. Each component preferably has a battery for providing power.