% This file contains an extracted local summary of land-surface % temperature results produced by the Berkeley Earth averaging % method for the location: % % 31.35 N, 120.63 E % % The Berkeley Earth method takes temperature observations from a large % collection of weather monitoring stations and produces an estimate of % the underlying global temperature field across all of the Earth's % land areas. Once this temperature field has been generated, it is % possible to estimate the temperature evolution of individual locations % simply by sampling the field at the locaiton in question. This % file contains such a local estimate. % % Temperatures are in Celsius. Uncertainties represent the 95% confidence % interval for statistical noise and spatial undersampling effects. Such % uncertainties are expected to account for the effects of random % noise as well as random biases affecting station trends and random % shifts in station baselines. The analysis framework is expected to be % robust against most forms of bias; however, the impact of some forms of % possible systematic bias is still being studied. % % % Berkeley Earth analysis for mean temperature on complete dataset % % % This analysis was run on 12-Oct-2013 00:45:15 % % Global results are based on 39348 time series % with 15244148 data points % % The current location is characterized by: % Country: China % Nearby Cities: Shanghai, Suzhou, Wuxi, Changzhou, Nantong, Jiaxing, Huzhou % Percent water in local neighborhood: 17.4 % % Temperature stations within 200 km: 22 % Temperature obeservations within 200 km: 11509 % % Note that all results reported here are derived from the full field % analysis and may use information from stations a great distance from the % target location when more local sources are not available. In general, % the temperature anomaly field has significant correlation extending over % greater than 1000 km, which allows even distant stations to provide some % insight at times when local coverage may be lacking. % % % Values are reported as missing (i.e. NaN) when station coverage near % this location becomes too low. Time averages over intervals with some % missing data will be reported as long as at least 75% of the necessary % values are available.