Water Vapour

 We report the results of the validation, long term stability and homogeneity analysis of the AIRWAVE dataset.
It consists in atmospheric water vapour total column (TCWV) retrieved using the measurements from the two
Thermal InfraRed (TIR) channels of the Along Track Scanning Radiometer (ATSR) instrument series,
on board the European Space Agency’s ERS-1, ERS-2 and ENVISAT satellites. The retrieval scheme,
named Advanced InfraRed WAter Vapour Estimator (AIRWAVE - Casadio et al., 2015), uses the instrument physical
characteristics,in combination with advanced radiative transfer models and a sea surface spectral emissivity database.
The retrievals therefore do not require algorithm tuning or adjustments to independent water vapour datasets.
The use of the dual view capability of the ATSR-type instruments, allows for the accurate and precise day-time and
night-time retrievals of cloud free TCWV over oceans. This new physical algorithm can be readily extended to
dual view radiometers similar to ATSR, such as the upcoming Sea and Land Surface Temperature Radiometer (SLSTR)
instrument on the European Copernicus Sentinel-3 satellite series.
The global validation of AIRWAVE TCWV, spanning from 1991 to 2012,
is carried out using the WMO soundings located on islands or close to coasts.
Validation results will be critically analysed and discussed.
Inter-comparisons with the Remote Sensing Systems Special Sensor Microwave Imager (RSS SSM/I) and ECMWF ERA-Interim
total water vapour column products have been carried out and results are discussed in detail
Finally, the consistency and homogeneity of the AIRWAVE TCWV data across the three ATSRs are analysed and discussed.

A merged time series of stratospheric water vapour built from HALOE and MIPAS data between 60S and 60N and 15 to 30 km and covering the years 1992 to 2012 was analyzed by multivariate linear regression including an 11-year solar cycle proxy. Lower stratospheric water vapour was found to reveal a phase-shifted anti-correlation with the solar cycle, with lowest water vapour after solar maximum. The phase shift is composed of an inherent constant time lag of about 2 years and a second component following the stratospheric age of air. The amplitudes of the water vapour response are largest close to the tropical tropopause (up to 0.35 ppmv) and decrease with altitude and latitude. Including the solar cycle proxy in the regression results in linear trends of water vapour being negative over the full altitude/latitude range, while without the solar proxy positive water wapour trends in the lower stratosphere were found. We conclude from these results that a solar signal seems to be generated at the tropical tropopause which most likely is imprinted on the stratospheric water vapour abundances and transported to higher altitudes and latitudes via the Brewer-Dobson circulation. Hence it is concluded that the tropical tropopause temperature at the final dehydration point of air may also be governed to some degree by the solar cycle. The negative water vapour trends obtained when considering the solar cycle impact on water vapour abundances can possibly solve the ``water vapour conundrum'' of increasing stratospheric water vapour abundances despite constant or even decreasing tropopause temperatures.

Limb measurements from SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartograpY) on Envisat in the near infrared can be used to retrieve the water vapour in the UTLS (upper troposphere and lower stratosphere). The UTLS is a region of special interest for a variety of dynamical and chemical processes in the atmosphere. Nevertheless, there are not many measurements which offer both, long data series and a dense coverage within the UTLS. The measurement period of SCIAMACHY between August 2002 and April 2012 allows retrieving water vapour profiles between about 12 to 23 km altitude with near global coverage for almost one decade.
Here, we present the latest data version for water vapour profiles from SCIAMACHY limb measurements. The data version was developed within the DFG research unit SHARP (Stratospheric Change and its Role for Climate Prediction). The most important change compared to V3.01 is the improvement of the aerosol correction. Additionally, updates of the Level 1c data, the spectral data base and other minor setup changes were applied. Due to the time-consuming retrieval process, calculations were performed using a Message Passing Interface (MPI) on the massively parallel supercomputing system of HLRN. The effect of these changes compared to V3.01 is shown and analysed and comparisons to water vapour from SCIAMACHY occultation are presented.

Water vapour plays a mayor role in the water cycle of the earth and is responsible for a large fraction of the green-house effect. Feed-back mechanisms with other trace-gases are a large uncertainty in climate prediction. Consequently, the monitoring of water vapour is crucial for studies about the earths climate and its evolution. The remote sensing of water vapour allows global observations of Total Column Water Vapour (TCWV) and the detection of local and global trends. Additionally, atmospheric correction, especially for ocean-color applications, is improved by accurate TCWV observations.

During the last years we have established a retrieval that derives TCWV from radiance measurements in the near-infrared. This spectral region is well suited because the sensitivity of the observation is in the boundary layer where most of the water vapour occurs. The 1D-var procedure minimizes the differences between measured and simulated top-of-atmosphere radiances in the water vapour absorption band around 900nm with the aid of optimal estimation and provides TCWV values and uncertainty estimates on a pixel basis. The retrieval uses only few auxiliary data and is applicable for all cloud-free land and ocean scenes. The pre-eminence of the method is that it can be straightforwardly adapted to sensors that measure radiance in the near-infrared. This sensor- independence enables the computation of long TCWV consistent time series and cross-comparison and calibration of the instruments. With the adaption to the Moderate Resolution Imaging Spectroradiometer (MODIS) we can fill the gap between the Medium Resolution Imaging Spectrometer (MERIS) and Ocean and Land Color Instrument (OLCI) TCWV time-line. In addition, the high spatial resolution of around 300m x 300m makes studies about small-scale variabilities of the TCWV possible.

In the presentation we will explain the general functionality of the universal TCWV retrieval and show validation studies for MERIS and MODIS TCWV that make use of several ground-based TCWV observations for land surfaces and TCWV data-sets derived from space-borne microwave sounders (e.g. MWR) for ocean surfaces.

Additionally, we discuss the issue of the limited temporal resolution of MERIS and OLCI observations by investigating the representatives of the 10:30 a.m. TCWV value to the daily mean TCWV. Therefor, we investigated the diurnal cycle of TCWV with the aid of a water vapour data-set from measurements of global distributed GPS stations.

Studies agreed on the power-law dependence of the water vapor [Nastrom et al. 1986] but the value of the scaling exponent differs a lot depending on the observation system (airborne, spaceborne, Lidar, IR), the scaling range, the vertical range [Fisher PhD Thesis, 2013]

Pressel and Collins [J. of Climate, 2012] quantified the spatial and seasonal variability of the water vapour scaling exponent from AIRS observations.

We will present the results of a similar approach applied to water vapour derived from microwave radiometers. Imagers as SSMI-S, AMSR-2 and GMI, sounders as SAPHIR and MHS, and nadir radiometers embedded on altimetry missions as AltiKa, Jason-2 and Sentinel-3 will be compared using both a classical spectral analysis and the structure functions as proposed by King 2014 [JGR] for the study of winds properties.

Seasonal maps are established to illustrate the spatial and the temporal variability of the water vapor scaling exponent (beta). A discussion is proposed on the impact of clouds screening. Quantitative differences between the missions are presented and the results are compared to previous studies (Pressel and Collins).