3.2.1 UK Met Office Data
The United Kingdom Meteorological Office (UKMO) assimilation system (Swinbank and O’Neill, 1994) is an outcome of assimilation of in-situ and remotely sensed data into a numerical forecast model of the stratosphere and troposphere. The outputs of the assi- milation are global fields of daily temperature, geopotential height, and wind components (meridional and zonal) at pressure levels from the surface up to 0.1-hPa. The assimila- tion system uses a global 42-level configuration of the Unified Mode, with a horizontal resolution of 2.5◦ and 3.75◦ steps in latitude and longitude, respectively, and have been run daily since October 1991 to produce near real-time global stratospheric analyses at 12 UTC every day. The analyses are output on the UARS standard levels from 1000-hPa to 0.316-hPa. The description of the original data assimilation system can be found in the work published by Swinbank and O’Neill (1994); the updated version which uses a three-dimensional variational data assimilation system is found in the work by Lorenc et al. (2000) and also Swinbank and Ortland (2003).
3.2.2 NCEP/NCAR Re-analysis Data
Temperature and wind fields used in this work are obtained from the National Centre for Environmental Prediction and National Centre for Atmospheric Research (NCEP/NCAR) reanalysis project available on the National Oceanic and Atmospheric Administration (NOAA) Climate Diagnostics Centre web page (http:/www.cdc.noaa.gov/). This co- operational project between NCEP an NCAR provides daily meteorological values on 2.5◦ latitude by 2.5◦ longitude resolution for 17 pressure levels (such as 1000, 925, 850, 700, 600, 500, 400, 300, 250, 200, 150, 100, 70, 50, 30, 20, and 10-hPa). The NCEP/NCAR re-analysis data is formed by the combination of the assimilated data from different me- teorological instruments which are scattered globally. The collection of data for reanalysis includes different observations at various countries over the land surface, ocean surface, upper-air such as Global radiosonde data, Comprehensive Ocean Atmosphere Data Set (COADS) marine surface data, Aircraft data, Surface landscape synoptic data, and sa- tellite sounder. The project began in 1991 as a spin off from the NCEP Climate Data Assimilation System (CDAS) project. The details of the NCEP/NCAR reanalyses execu- tion method, data analysis, data assimilation and comprehensive output variables are well explained in work published by Kalnay et al. (1996).
3.2.3 ECMWF ERA-40 Re-analysis Data
In this thesis the European Centre for Medium-Range Weather Forecast Re-Analysis for 40 years (ECMWF ERA-40) horizontal wind fields extracted on a 1.125◦ by 1.125◦ grid from 1000 to 1-hPa pressure levels have been used to study the prevailing meteorological and dynamical conditions during the Southern Hemisphere major SSW by deriving the Eliassen-Palm (E-P) flux. The ECMWF ERA-40 data and its documentation can be downloaded from the ECMWF website, http://www.ecmwf.int/research/era/.
The ECMWF ERA-40 is a re-analysis of the meteorological field variables starting from September 1957 to August 2002 by the ECMWF in collaboration with a number of other institutes. The ERA-40 is an improved version of ERA-15, with one of the most important improvements being that the ERA-40 directly assimilates the Television Infrared Obser- vation Satellites (TIROS) Operational Vertical Sounder (TOVS) and Advanced TOVS radiances, as opposed to retrieved temperature and wind profiles. The data is available at 23 standard pressure levels spanning from 1000 to 1-hPa, and as well as at each of the 60 levels of the assimilation model.
3.2.4 CIRA-86 Model
The COSPAR International Reference Atmosphere (CIRA-86) climatological model is a compilation of experimental and theoretical data. The CIRA-86 reference climatologies extend from 0 to 120 km. The model is based mainly on the nadir (SCR) experiment on board the NIMBUS-6 satellite from 1975 to 1978 . The detail of the CIRA-86 zonal mean temperature, geopotential height, and zonal wind has been described in a study published by Barnett and Corney (1985) and Fleming et al. (1990).
Chapter 4
LIDAR Observations
4.1 Introduction
Temperature monitoring in the atmosphere is important as it controls the rate of chemical reactions and thus ozone abundance. The middle atmospheric temperature is an important parameter because it is a combined manifestation of the dynamical, radiative, and chemical processes occurring in the middle atmosphere (Singh et al., 1996). The study of the middle atmospheric thermal structure is also important for understanding the coupling between different regions of the atmosphere. The temperature structure in the middle atmosphere has been studied for several decades using a variety of techniques. The first studies used rocketsondes and falling spheres to measure temperature profiles up to 60- 90 km, but with relatively poor accuracy due to uncertain radiative and aerodynamic heating corrections (Schmidlin, 1981). However, the first experimental (Kent and Wright, 1970) and systematic (Hauchecorne and Chanin, 1980) temperature profiles derived from Rayleigh LIDAR measurements of the relative density of the middle atmosphere provided improved accuracy and vertical resolution.
Although many instruments are used to study the middle atmospheric temperature (e.g.
rockets, satellite, radiometers), LIDARs are found to be more accurate and efficient com- pared to the other instruments. They also provide long-term data series relatively devoid of instrumental drift. Integration of the measurements over several hours filters away most of the gravity wave-like short scale disturbances. Thus, the Rayleigh LIDAR has emerged as the most important ground based technique to study the structure and dynamics of the middle atmosphere (Hauchecorne and Chanin, 1983; Chanin, 1991; Leblanc et al., 1998;
Whiteway and Carswell, 1994; Sivakumar et al., 2003).
The climatology of the middle atmospheric temperature has been studied over the past decades using LIDARs and other instruments [Wang et al. (1992); Namboothiri et al.
(1999a); Labitzke and Naujokat (2000); Sivakumar et al. (2003); Chang et al. (2005); Ar- gall and Sica (2007); and references therein]. Hauchecorne et al. (1991) used the Rayleigh
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LIDAR from two stations in France (OHP, 44◦N, 6◦E; BIS, 44◦N, 1◦W) for the first time to study the climatology of the mid-latitude middle atmosphere temperature. Sivakumar et al. (2003) studied the thermal structure of the middle atmosphere over Gadanki (13.5◦N 79.2◦E), India, using Rayleigh LIDAR data and also compared the LIDAR results with Halogen Occultation Experiments (HALOE) on board the Upper Atmosphere Research Satellite (UARS), the CIRA-86 model and the Mass Spectrometer Incoherent Scatter Extended-1990 (MSISE-90) model. More recently, Li et al. (2008) applied the linear re- gression analyses to a 13.5-year long (January 1994 to June 2007) de-seasonalized monthly mean temperature time series for each 1 km altitude bin between 15 and 85 km, measured by the Jet Propulsion Laboratory Rayleigh-Raman LIDAR at Mauna Loa Observatory, Hawaii (19.5◦N, 155.6◦W). Their regression analysis included components representing the Quasi-Biennial Oscillation (QBO), the El Ni˜no-Southern Oscillation (ENSO) and the 11-year solar cycle. The analyses revealed the dominance of the QBO (1-3 K) in the stra- tosphere and mesosphere, and a strong winter signature of ENSO in the troposphere and lowermost stratosphere (∼1.5 K/MEI).
Comparisons between LIDAR temperature observations and observations made using other well established methods/techniques provide a very good opportunity to understand the middle atmosphere thermal structure better. Satellite measurements offer the best me- thod for providing the temperature structure over the globe with satisfactory tempo- ral coverage. However, their height resolution is poor compared to most ground-based instruments. Thus, comparing and quantifying the differences between space-based and ground-based instruments can compensate for the limitations. There have been a num- ber of studies which report on comparisons between Rayleigh LIDAR observations and other instruments (Clancy et al., 1994; Sivakumar et al., 2003; Xu et al., 2006; Argall and Sica, 2007; Dou et al., 2009). Namboothiri et al. (1999a) compared LIDAR measu- red temperature profiles with rockets, satellite measured profiles and the COSPAR In- ternational Reference Atmosphere 1986 (CIRA-86) model. They found that the LIDAR profiles are in fair agreement with the rockets, satellite measurements and the CIRA-86 model. Recently, Dou et al. (2009) studied the seasonal oscillations of the middle at- mosphere temperature observed using Rayleigh LIDARs at six different locations from low to high latitudes within the Network for the Detection of Atmosphere Comparison Change (NDACC). They performed comparisons with the results derived from the Soun- ding of the Atmosphere using Broadband Emission Radiometry (SABER) on board the Thermosphere–Ionosphere–Mesosphere-Energetics and Dynamics (TIMED) satellite ob- servations, and found good agreement at similar latitudes.
The most recent studies which employed the Durban LIDAR temperature data include a study by Moorgawa et al. (2007) which describes the Durban LIDAR system for tem- perature measurements, and also reported a good agreement between the LIDAR and South African Weather Service (SAWS) radiosonde temperature for the lower stratosphere, (∼20-27 km). Bencherif et al. (2007) used data from the Durban Rayleigh-Mie LIDAR,
CHAPTER 4. LIDAR OBSERVATIONS 45
MeteoSat, SAGE-2 experiments, and ECMWF meteorological analysis to study the lower stratospheric aerosols over South Africa and their link to large scale transport across the southern subtropical barrier. Also, Bencherif et al. (2000) performed the first validation of the stratospheric temperature profiles obtained by the Durban Rayleigh LIDAR.
In this, the Rayleigh LIDAR measurements made over Durban (29.9◦S, 31.0◦E) were used to study the stratosphere-mesospheric thermal structure over Durban. LIDAR monthly temperature mean profiles are also compared with SABER observations, temperature data from HALOE, and the CIRA-86 model. Seasonal variations of temperature climatology of the Durban LIDAR are obtained and compared with a similar Rayleigh LIDAR system situated in Reunion (20.8◦S, 55.5◦E). The results obtained in this work are also discussed and compared with results available in the literature. Most part of this chapter content has been published in a study by Mbatha et al. (2010a) and Mbatha et al. (2011).