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  • The UK Universities Global Atmospheric Modelling Programme (UGAMP) ozone climatology project. This dataset contains a 3-dimensional climatology of ozone monthly means, combining various satellite observations and ozone sonde data. The data are global and covers 1986. Each file contains a ligne of text followed by the variable itself, in free format. Every single three-dimensional field var is stored as (((var(i, j, k), i=1, 144), j=1, 73), k=1, 47) where i is the longitude index (from 0°E to 357.5°E by 2.5°); j is the latitude index (from South Pole to North Pole by 2.5°); k is the level index (from top to bottom). Every two-dimensional field (zonal means) is stored as ((var(j, k), j=1, 73), k=1, 47) with the same conventions as above.

  • CCMVal was a large international effort to improve understanding of Chemistry-Climate Models (CCMs) and their underlying GCMs (General Circulation Models) through process-oriented evaluation, along with discussion and coordinated analysis of science results. The first round of CCMVal (CCMVal-1) evaluated only a limited set of key processes in the CCMs, focusing mainly on dynamics and transport. This dataset contains LMDZrepro model output from the WMO 2006 DYNAMICS experiment run by the Institut Pierre Simon Laplace, France.

  • The Bolton Experiment was an experimental test of the use of microwave attenuation to improve rainfall estimates in urban areas, and hence to enhance flood warning. Data was collected from microwave and radar links and a number of telemetered tipping bucket raingauges. The dataset contains microwave, raingauge and radar data. It also contains data analysis to extract information from the link attenuation data on path-averaged rainfall rate, and comparison with the results with those obtained from the raingauges and the radar. The dataset is now public.

  • CCMVal was a large international effort to improve understanding of Chemistry-Climate Models (CCMs) and their underlying GCMs (General Circulation Models) through process-oriented evaluation, along with discussion and coordinated analysis of science results. The first round of CCMVal (CCMVal-1) evaluated only a limited set of key processes in the CCMs, focusing mainly on dynamics and transport. This dataset contains GEOSCCM model output from the WMO 2006 REF1 experiment run by the National Aeronautics and Space Administration (NASA).

  • The UK Universities Global Atmospheric Modelling Programme (UGAMP) ozone climatology project. This dataset contains a 3-dimensional climatology of ozone averages, combining various satellite observations and ozone sonde data. The data are global and covers 1985-1989. Each file contains a ligne of text followed by the variable itself, in free format. Every single three-dimensional field var is stored as (((var(i, j, k), i=1, 144), j=1, 73), k=1, 47) where i is the longitude index (from 0°E to 357.5°E by 2.5°); j is the latitude index (from South Pole to North Pole by 2.5°); k is the level index (from top to bottom). Every two-dimensional field (zonal means) is stored as ((var(j, k), j=1, 73), k=1, 47) with the same conventions as above.

  • Evaluation of the Ozone and Water Vapour Datasets of the 40-Year European Re-analysis of the Global Atmosphere Upper Troposphere Lower Stratosphere (UTLS) Round 2 project led by Prof. A. O Neill, Dr W. Lahoz and Prof. B. Hoskins, Centre for Global Atmospheric Modelling, Department of Meteorology, University of Reading. This dataset contains comparisons between the ERA40 water vapour field output and measurements from the MOZAIC research aircraft instrumentation and the Halogen Occultation Experiment (HALOE) and Microwave Limb Sounder (MLS) instruments on board the Upper Air Research Satellite (UARS).

  • CCMVal was a large international effort to improve understanding of Chemistry-Climate Models (CCMs) and their underlying GCMs (General Circulation Models) through process-oriented evaluation, along with discussion and coordinated analysis of science results. The first round of CCMVal (CCMVal-1) evaluated only a limited set of key processes in the CCMs, focusing mainly on dynamics and transport. This dataset contains LMDZrepro model output from the WMO 2006 REF1 experiment run by the Institut Pierre Simon.

  • MOHMAT, (Met Office Historical Marine Air Temperature) is a gridded dataset of marine air temperature anomalies covering the period 1856-2006. The current version of the dataset is MOHMAT4, which is described in reference below (under Doc tab). MOHMAT is produced by taking in-situ measurements of MAT from ships and buoys, rejecting measurements which fail quality checks, converting the measurements to anomalies by subtracting climatological values from the measurements, and averaging the resulting anomalies on a 5 by 5 degree monthly grid. Note that only night-time data are used, because day-time data are corrupted by heat island effects. Up to 1996 the measurements used are those in the U.K. Marine Data Bank; more recent years use data coming in through the GTS. MOHMAT is no longer updated. After gridding the anomalies, bias corrections are applied to remove spurious trends caused by changes in ship deck heights and various unusual operational practices, and the data are smoothed to reduce noise. The data are provided by the Met Office.

  • The Meteorological Research Flight (MRF) was a Met Office facility, which flew a well-instrumented C-130 Hercules aircraft for atmospheric research purposes. This dataset contains airborne atmospheric and chemistry measurements taken on board the Met Office C-130 Hercules aircraft flight A753 for the Atmospheric Chemistry and Transport of Ozone in the upper troposphere-lower stratosphere (UTLS) (ACTO) campaign. The flight was located over the Irish sea. The purpose of the flight was to investigate further the various filaments of air that were sampled in flight A752. That is polluted air, having origins in the Mediterranean region; clean marine boundary layer air; ozone-rich, dry upper tropospheric air (from upper tropospheric jet) and also polluted boundary layer air, which has been uplifted from N. America. The region should be very structured having many different characteristics. The filaments of air were expected to be aligned zonally, sloping downwards to the North. The flight was successful in that some of the filaments were found. However, the filaments were not found in the expected area. During a level hold at FL160 (for air traffic) and at the beginning of the first run at FL170 (NOxy calibrations), a dry ozone-rich filament was sampled. Later during the same run, air with moderately high ozone (around 70 ppb), high relative humidity and elevated peroxide was observed. At the subsequent level (FL240) ozone mixing ratios were generally lower (around 45-50 ppb) and the CN count was elevated (2500). However, during the turn at ca. 12:10 on FL240 (SE corner of the flight), another dry, ozone-rich filament was found. A further filament was expected to the North but this was not found. Towards the end of the flight further investigations were made at FL170, in order to try to find the first area of high ozone air (i.e. the air that was sampled during the first NOxy cal run). This air was found but interestingly, the ozone-rich dry air also correlated with high PAN and black carbon. The instruments generally worked well. The FWVS was adjusted in flight and then found to maintain a good correlation with the GE. Neither the CO nor the HCHO were flown due to previously existing faults. There was a problem with the peroxide pump but this was not until the end of the flight. Meteorology The meteorological situation was dominated by high pressure, centred to the north of Scotland. The south of the country was in a more showery regime. However, not much cloud was observed during flight: small cumulus, broken stratocumulus and some cirrus, were observed at times.

  • The UK Universities Global Atmospheric Modelling Programme (UGAMP) ozone climatology project. This dataset contains a 3-dimensional climatology of ozone monthly means, combining various satellite observations and ozone sonde data. The data are global and covers 1988. Each file contains a ligne of text followed by the variable itself, in free format. Every single three-dimensional field var is stored as (((var(i, j, k), i=1, 144), j=1, 73), k=1, 47) where i is the longitude index (from 0°E to 357.5°E by 2.5°); j is the latitude index (from South Pole to North Pole by 2.5°); k is the level index (from top to bottom). Every two-dimensional field (zonal means) is stored as ((var(j, k), j=1, 73), k=1, 47) with the same conventions as above.