Several times in the past, philanthropists have stepped forward to support work on climatoloeical data-sets, aimed either at preserving them or making them more readily available for researchers. Perhaps it is time again for this type of philanthropy.

Existing adjustment procedures for precipitation measured by the 8-in. standard nonrecording rain gauge (SNRG) take into account gauge undercatch mostly due to wind-induced turbulence over its orifice. The goal of this paper is to "reduce" the measurements of the two most commonly used U.S. recording rain gauges (SRGs) to those for a hypothetical SNRG at the same site and use established relationship to adjust their readings to less biased values. This will allow gauge-specific adjustments for each gauge/precipitation type to secure less biased homogeneous precipitation time series and facilitate blending of precipitation information from different sources/networks.A significant portion of the U.S, rain gauges are automated recording gauges. A majority of the gauges of the National Oceanic and Atmospheric Administration Hourly Precipitation Network are unshielded Fischer and Porter recording rain gauges (FP) that have gradually replaced weighing recording rain gauges (WG). There are more than 1400 sites where the unshielded SNRG and FP are collocated (and more than 100 sites for SNRG and WG). Daily precipitation from these sites from 1982 to 1996 were partitioned into three categories: rainfall, frozen, and mixed precipitation. The hourly records from recording gauges were totaled over the 24-h-long period specific to each station to match the observation rimes of the SRGs and compared with the daily SNRG records. The comparison of the rain and snow catch of WG and SNRG shows nearly equivalent measurements. Mixed precipitation is the most troublesome type to register for WG and averages 7% less than collocated SNRG. Rain catch of the FP averages 5% less than SNRG and is not strongly related to climate conditions and/or surroundings of meteorological sites. Also, FP observations of frozen precipitation can be as high as 105% and as low as 70% compared to SNRG with an average of 90% (85% over the Great Plains). In open, windy locations, the SNRG can underestimate frozen precipitation by 50% or more. The authors' estimates indicate that FP underestimates frozen precipitation even more than SNRG, and the level of the underestimation is a function of wind speed and gauge exposure.

To capture the global land surface temperature signal in a timely way, a blend of traditional long-term in situ climatic data sets, combined with real time Global Telecommunications System monthly CLIMAT summaries is employed. For the global sea surface, long-term ship data climatologies are combined with a blend of ship, buoy, and satellite data to provide the greatest possible coverage over the oceans. The result is a global century-scale surface temperature index that closely parallels other widely published global surface temperature measurements and can be updated monthly a week or two after the end of a month.

The need to correct systematic errors in gauge-measured precipitation has been more widely acknowledged, as the magnitude of the errors and their variation between gauges became

The American Meteorological Society held its Sixth Symposium on Education in conjunction with the 77th Annual Meeting in Long Beach, California. The theme of the symposium was "Atmospheric and Oceanographic Education:Teaching about the Global Environment." Thirty-eight oral presentations and 37 poster presentations summarized a variety of educational programs or examined educational issues for both the precollege and university levels. There was also a joint session with the Eighth Symposium on Global Change Studies and a special session on "home pages" to promote popular meteorological education. Over 200 people representing a wide spectrum of the Society attended one or more of the sessions in this two-day conference where they increased their awareness of teaching about the global environment.

Because of shortcomings in the current wind chill formulation, which did not consider the metabolic heat generation of the human body, a new formula is proposed for operational implementation. This formula, referred to as the Steadman wind chill, is based on peer-reviewed research including a heat generation and exchange model of an appropriately dressed person for a range of low temperatures and wind speeds. The Steadman wind chill produces more realistic wind chill equivalents than the current NWS formulation. It is easy to determine from tables (calculated by application of a quadratic fit in both U.S. and metric units) with values accurate to within 1 degrees C.

The history of climatic divisions in the contiguous United States has been pieced together from fragmentary documentation. Each of the 48 contiguous states has been subdivided into climatic divisions. Divisional boundaries are now standardized, and a set of climatic variables for time-invariant divisional boundaries has been compiled for the period of record beginning in 1895. This paper documents the origins of climatic divisions, the computational methodology of an area-invariant divisional dataset maintained by the National Climatic Data Center, and the strengths and weaknesses of divisional data.

Adjustment procedures for reducing the bias in precipitation point measurements of standard U.S. rain gauges are discussed. The procedures presented here employ information about wind speed variations over the gauge orifice during precipitation events and extensive metadata files which trace the history of precipitation measurements at each site throughout the period of instrumental observations (gauge type, exposure, and site climatology). The metadata required for this more sophisticated method has been compiled for about 1500 U.S. stations. A description of this metadata is provided, and examples of the application of this adjustment procedure are shown. However, reconstruction of precipitation over rough terrain from a network of adjusted point precipitation values still remains a problem for further studies.

A framework is presented to quantify observed changes in climate within the contiguous United States through the development and analysis of two indices of climate change, a Climate Extremes Index (CEI) and a U.S. Greenhouse Climate Response Index (GCRI). The CEI is based on an aggregate set of conventional climate extreme indicators, and the GCRI is composed of indicators that measure changes in the climate of the United States that have been projected to occur as a result of increased emissions of greenhouse gases.The CEI supports the notion that the climate of the United States has become more extreme in recent decades, yet the magnitude and persistence of the changes are not large enough at this point to conclude that the increase in extremes reflects a nonstationary climate. Nonetheless, if impacts due to extreme events rise exponentially with the index, then the increase may be quite significant in a practical sense. Similarly, the positive trend of the U.S. GCRI during the twentieth century is consistent with an enhanced greenhouse effect. The increase is unlikely to have arisen due to chance alone (there is about a 5% chance). Still, the increase of the GCRI is not large enough to unequivocally reject the possibility that the increase in the GCRI may be the result of other factors, including natural climate variability, and the similarity between the change in the GCRI and anticipated changes says little about the sensitivity of the climate system to the greenhouse effect. Both indices increased rather abruptly during the 1970s, a time of major circulation changes over the Pacific Ocean and North America.

It has been established that minimum temperatures have been increasing with time at a higher rate than maximum temperatures for the past several decades, most prominently for large parts of the Northern Hemisphere land mass, but in other areas as well. We demonstrate that (for China, at least) this increase in nighttime temperatures is not necessarily the result of changes in cloud cover for the period 1951–1990.

The release of greenhouse gases is expected to lead to substantial future warming. The global mean temperature has indeed risen in recent decades. The causes of the observed warming, and its relation to the greenhouse gas buildup are, however, still debated. One important aspect of the observed temperature change relates to its asymmetry during the day and night. The day-night temperature difference over land in North America, most of Eurasia, Oceania, and portions of Africa and Australia shows a decrease since about 1950. The changes of the daily mean temperature in these areas are principally due to the rising night or early morning temperature, and are accompanied by increasing cloudiness. Their results support the notion that the increase of cloud cover, possibly due to industrial sulfur emissions, mitigates the greenhouse warming. The causes of the changing diurnal temperature range and of the increasing cloudiness will have to be clarified and the future SO{sub 2} emissions reliably projected before any trustworthy prediction of future climates can be made. 37 refs., 7 figs., 2 tabs.

Several essential aspects of weather observing and the management of weather data are discussed as related to improving knowledge of climate variations and change in the surface boundary layer and the resultant consequences for socioeconomic and biogeophysical systems. The issues include long-term homogeneous time series of routine weather observations; time- and space-scale resolution of datasets derived from the observations; information about observing systems, data collection systems, and data reduction algorithms; and the enhancement of weather observing systems to serve as climate observing systems.Although much has been learned from existing weather networks and methods of data management, the system is far from perfect. There are several vital areas that have not received adequate attention. Particular improvements are needed in the interaction between network designers and climatologists; operational analyses that focus on detecting and documenting outliers and time-dependent biases within datasets; developing the means to cope with and minimize potential inhomogeneities in weather observing systems; and authoritative documentation of how various aspects of climate have or have not changed. In this last area, close attention must be given to the time and space resolution of the data. In many instances the time and space resolution requirements for understanding why the climate changed are not synonymous with understanding how, it has changed or varied. This is particularly true within the surface boundary layer. A standard global daily/monthly climate message should also be introduced to supplement current Global Telecommunication System's CLIMAT data. Overall, a call is made for improvements in routine weather observing, data management, and analysis systems. Routine observations have provided (and will continue to provide) most of the information regarding how the climate has changed during the last 100 years affecting where we live, work, and grow our food.

A unique set of data from Valdai, Russia, (previously unreported in the United States) is used to evaluate the ubiquitous standard 8-in.-diameter raingage that has been used for over 100 years at tens of thousands of United States stations. The results of the Valdai analyses (where the 8-in. raingage measurements had been analyzed during 4 years of parallel observations with the etalon raingage) are consistent with other findings summarized in this paper. Rain undercatch (unshielded) is about 4%. Evaporation losses from the raingage and wetting losses (where part of the water stays on the funnel and bucket walls of the raingage and is not measured) have been estimated and were found to be fairly small. To put this in perspective, snow undercatch (as reported by others) can be several tens of percent for windy, unshielded sites.

Climate models with enhanced greenhouse gas concentrations have projected temperature increases of 2-degrees to 4-degrees-C, winter precipitation increases of up to 15 percent, and summer precipitation decreases of 5 to 10 percent in the central United States by the year 2030. An analysis of the climate record over the past 95 years for this region was undertaken in order to evaluate these projections. Results indicate that temperature has increased and precipitation decreased both during winter and summer, and that the ratio of winter-to-summer precipitation has decreased. The signs of some trends are consistent with the projections whereas others are not, but none of the changes is statistically significant except for maximum and minimum temperatures, which were not among the parameters predicted by the models. Statistical models indicate that the greenhouse winter and summer precipitation signal could have been masked by natural climate variability, whereas the increase in the ratio of winter-to-summer precipitation and the higher rates of temperature change probably should have already been detected. If the models are correct it will likely take at least another 40 years before statistically significant precipitation changes are detected and another decade or two to detect the projected changes of temperature.

During the past five years, the National Weather Service (NWS) has replaced over half of its liquid-in-glass maximum and minimum thermometers in wooden Cotton Region Shelters (CRSs) with thermistor-based Maximum-Minimum Temperature Systems (MMTSs) housed in smaller plastic shelters. Analyses of data from 424 (of the 3300) MMTS stations and 675 CRS stations show that a mean daily minimum temperature change of roughly +0.3-degrees-C, a mean daily maximum temperature change of -0.4-degrees-C, and a change in average temperature of -0.1-degrees-C were introduced as a result of the new instrumentation. The change of -0.7-degrees-C in daily temperature range is particularly significant for climate change studies that use this element as an independent variable. Although troublesome for climatologists, there is reason to believe that this change (relative to older records) represents an improvement in absolute accuracy. The bias appears to be rather sharp and well defined. Since the National Climatic Data Center (NCDC) station history database contains records of instrumentation, adjustments for this bias can be readily applied, and we are reasonably confident that the corrections we have developed can be used to produce homogeneous time series of area-average temperature.