Enhancing Tropospheric Humidity Data Records from Satellite Microwave and Radiosonde Sensors
Doctoral thesis, 2015
Water vapor is the most dominant greenhouse gas and plays a critical role in the climate by regulating the Earth's radiation budget and hydrological cycle. A comprehensive dataset is required to describe the temporal and spatial distribution of water vapor, evaluate the performance of climate and weather prediction models in terms of simulating tropospheric humidity, and understand the role of water vapor and its feedback in the climate system. Satellite microwave and radiosonde measurements are two important sources of tropospheric humidity. However, both datasets are subject to errors and uncertainties. The goal of this dissertation was to develop techniques for quantifying and correcting errors in both radiosonde and microwave satellite data. These techniques can be used to homogenize the datasets in order to develop tropospheric humidity climate data records.
The quality of operational radiosonde data were investigated for different sensor types. It was found that the use of a variety of sensors over the globe introduces temporal and spatial errors in the data. Further, it was shown that the daytime radiation dry bias, which is one the most important errors in radiosonde data, depends on both sensor type and radiosonde launch time. The error significantly decreases if daytime data are collected near sunrise or sunset.
Radiometric errors in satellite data were investigated using both intercomparison of coincident observations as well as validation versus high-quality radiosonde and global positioning system radio occultation data. The results showed that the data from recently launched microwave sounders have a good accuracy relative to each other and simulated data.
However, the absolute accuracy of the microwave satellite data can still not be validated due to the lack of reference measurements. In addition, a novel technique for correcting geolocation errors in microwave satellite data was developed based on the difference between ascending and descending observations along the coastlines. Using this method, several important errors including timing errors up to a few hundred milliseconds, and sensor mounting errors up to 1.2 degree were found in some of the microwave instruments.
Finally, since satellite data are indirect measurements, a method was developed to transform satellite radiances from different water vapor channels to layer averaged humidity. The technique is very fast because radiative transfer calculations are only required to determine the empirical coefficients.
sal EA, Hörsalsvägen 11, Chalmers, Göteborg
Opponent: Dr. Roger Saunders, UK Met Office, Exeter, UK