ﻻ يوجد ملخص باللغة العربية
[Abridged] This paper describes the creation of HadISD: an automatically quality-controlled synoptic resolution dataset of temperature, dewpoint temperature, sea-level pressure, wind speed, wind direction and cloud cover from global weather stations for 1973--2011. The full dataset consists of over 6000 stations, with 3427 long-term stations deemed to have sufficient sampling and quality for climate applications requiring sub-daily resolution. As with other surface datasets, coverage is heavily skewed towards Northern Hemisphere mid-latitudes. The dataset is constructed from a large pre-existing ASCII flatfile data bank that represents over a decade of substantial effort at data retrieval, reformatting and provision. These raw data have had varying levels of quality control applied to them by individual data providers. The work proceeded in several steps: merging stations with multiple reporting identifiers; reformatting to netCDF; quality control; and then filtering to form a final dataset. Particular attention has been paid to maintaining true extreme values where possible within an automated, objective process. Detailed validation has been performed on a subset of global stations and also on UK data using known extreme events to help finalise the QC tests. Further validation was performed on a selection of extreme events world-wide (Hurricane Katrina in 2005, the cold snap in Alaska in 1989 and heat waves in SE Australia in 2009). Although the filtering has removed the poorest station records, no attempt has been made to homogenise the data thus far. Hence non-climatic, time-varying errors may still exist in many of the individual station records and care is needed in inferring long-term trends from these data. A version-control system has been constructed for this dataset to allow for the clear documentation of any updates and corrections in the future.
Large area arrays composed by dispersed stations are of major importance in experiments where Extended Air Shower (EAS) sampling is necessary. In those dispersed stations is mandatory to have detectors that requires very low maintenance and shows goo
Recently, we have struck the balance between the information freshness, in terms of age of information (AoI), experienced by users and energy consumed by sensors, by appropriately activating sensors to update their current status in caching enabled I
Fuel moisture has a major influence on the behavior of wildland fires and is an important underlying factor in fire risk assessment. We propose a method to assimilate dead fuel moisture content observations from remote automated weather stations (RAW
We present the activities of the New Physics working group for the Physics at TeV Colliders workshop (Les Houches, France, 30 May-17 June, 2011). Our report includes new agreements on formats for interfaces between computational tools, new tool devel
Spatially and temporally explicit canopy water content (CWC) data are important for monitoring vegetation status, and constitute essential information for studying ecosystem-climate interactions. Despite many efforts there is currently no operational