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The NOAA National Climatic Data Center maintains tables for temperature and precipitation extremes in each of the U.S. states. Many of these tables were several years out of date, however, and therefore did not include a number of recent record-setting meteorological observations. Furthermore, there was no formal process for ensuring the currency of the tables or evaluating observations that might tie or break a statewide climate record. This paper describes the evaluation and revision of the statewide climate-extremes tables for all-time maximum and minimum temperature, greatest 24-h precipitation and snowfall, and greatest snow depth (the five basic climate elements observed on a daily basis by the NOAA Cooperative Weather Network). The process resulted in the revision of 40% of the values listed in those tables and underscored both the necessity of manual quality-assurance methods and the importance of continued climate-monitoring and data-rescue activities to ensure that potential record values are not overlooked. [ABSTRACT FROM AUTHOR]

This paper evaluates the quality of real-time seasonal probabilistic forecasts of the extreme 15%% tails of the climatological distribution of temperature and precipitation issued by the International Research Institute for Climate and Society (IRI) from 1998 through 2009. IRI's forecasts have been based largely on a two-tiered multimodel dynamical prediction system. Forecasts of the 15%% extremes have been consistent with the corresponding probabilistic forecasts for the standard tercile-based categories; however, nonclimatological forecasts for the extremes have been issued sparingly. Results indicate positive skill in terms of resolution and discrimination for the extremes forecasts, particularly in the tropics. Additionally, with the exception of some overconfidence for extreme above-normal precipitation and a strong cool bias for temperature, reliability analyses suggest generally good calibration. Skills for temperature are generally higher than those for precipitation, due both to correct forecasts of increased probabilities of extremely high (above the upper 15th percentile) temperatures associated with warming trends, and to better discrimination of interannual variability. However, above-normal temperature extremes were substantially underforecast, as noted also for the IRI's tercile forecasts. [ABSTRACT FROM AUTHOR]

Vegetation around the Daihai Lake, northern China, is very sensitive to climate changes. In this paper, pollen-based quantitative climate reconstructions using three methods [weighted averaging partial least squares method (WAPLS), modern analog technique (MAT), and pollen response surface method (PRS)] were conducted to obtain robust reconstructions of Holocene climate changes in the Daihai Lake area. The result obtained by the three methods all consistently show the annual precipitation to have been 50–100 mm lower in the early Holocene, 100–200 mm higher in the Mid-Holocene, and 50–100 mm lower again in the late Holocene than at present. The WAPLS and the MAT methods also show quasi-synchronous oscillations of the mean annual temperature (Ta); 1°–2°C lower in the Early Holocene and 1°–3°C higher in the Mid-Holocene than today. The time period from 6200 to 5100 cal yr BP was the wettest and the warmest interval, with an annual precipitation (Pa) greater than 550 mm and mean annual temperature Ta higher than 6.5°C. Several cold and dry events can be identified to occur about 8200, 6000, and 4400 cal yr BP, with an annual precipitation less than 400 mm and a mean annual temperature colder than 4.5°C, respectively. The mean temperature of the warmest month (Tw) as reconstructed using both WAPLS and MAT methods was relatively stable during the Holocene, fluctuating about ±2°C relative to the present level, but the PRS method suggests more varied Tw values in both amplitude and frequency. After 1500 cal yr BP, no consistent pattern can be observed from these three different analyses, probably because of the impact of intensified human disturbances on the natural vegetation. The fluctuations of annual precipitation (Pa) correspond to that observed in Dongge Cave in southern China. The differences might be linked to Indian monsoon and East Asia monsoon climates or caused by the different degree of dating precision, different temporal resolution, and different sensitive response of climate proxies to the climate variations. [ABSTRACT FROM AUTHOR]

This paper examines variability in surface climate and the relationship with two circulation indices using recently produced 200-250 year long European daily and monthly climatic series. Assessments are made of the influence of circulation indices (zonal over western Europe and average pressure over central Europe) on regional temperature, precipitation and drought series for northern and central Europe. Changes in the circulation are shown to be very important during the winter in northern Europe, but only over western and central Europe in summer. Circulation indices in winter, however, only explain up to 25% of surface-climate variability and, except for the British Isles, do not explain any decadal and longer timescale variability in summer. Extreme temperatures and growing-season and frost-season durations and degree-day series are calculated for four sites (Central England, Stockholm, Uppsala and St. Petersburg). Degree-day counts are shown to be very strongly correlated (r > 0.9) to average extended summer ('growing' season, May to September) and extended winter ('frost' season, October to April) temperatures. Durations of the growing and frost seasons are only weakly correlated (r ∼ 0.2-0.4) with the appropriate extended seasonal temperatures or degree-day counts. Warmer growing/frost seasons, therefore, need not necessarily be longer/shorter. Counts of extremely warm days in each year are more highly correlated with the growing-season mean temperature than with coldseason temperature. Similarly, counts of extremely cold days in each year are more highly correlated with cold-season temperature than with growing-season temperature. Both the growing-season temperature and the corresponding degree-day counts clearly show warmer temperatures over all series in Fennoscandia before 1860. Over central Europe, and for the Central England temperature series, growing seasons now are of similar warmth to those before 1860. Annually averaged temperatures across the three regions indicate long-term warming which is, however, almost entirely the result of warming during the October to April period. [ABSTRACT FROM AUTHOR]