Carlos J. Jimenez

Early validation analyses of atmospheric profiles from EOS MLS on the aura Satellite

We present results of early validation studies using retrieved atmospheric profiles from the Earth Observing System Microwave Limb Sounder (MLS) instrument on the Aura satellite. Global results are presented for MLS measurements of atmospheric temperature, ozone, water vapor, hydrogen chloride, nitrous oxide, nitric acid, and carbon monoxide, with a focus on the January-March 2005 time period. These global comparisons are made using long-standing global satellites and meteorological datasets, as well as some measurements from more recently launched satellites. Comparisons of MLS data with measurements from the Ft. Sumner, NM, September 2004 balloon flights are also presented. Overall, good agreement is obtained, often within 5% to 10%, but we point out certain issues to resolve and some larger systematic differences; some artifacts in the first publicly released MLS (version 1.5) dataset are noted. We comment briefly on future plans for validation and software improvements.

SMOS Brightness Temperature Angular Noise: Characterization, Filtering, and Validation

The 2-D interferometric radiometer on board the Soil Moisture and Ocean Salinity (SMOS) satellite has been providing a continuous data set of brightness temperatures, at different viewing geometries, containing information of the Earths surface microwave emission. This data set is affected by several sources of noise, which are a combination of the noise associated with the radiometer itself and the different views under which a heterogeneous target, such as continental surfaces, is observed. As a result, the SMOS data set is affected by a significant amount of noise. For many applications, such as soil moisture retrieval, reducing noise from the observations while keeping the signal is necessary, and the accuracy of the retrievals depends on the quality of the observed data set. This paper investigates the averaging of SMOS brightness temperatures in angular bins of different sizes as a simple method to reduce noise. All the observations belonging to a single pixel and satellite overpass were fitted to a polynomial regression model, with the objective of characterizing and evaluating the associated noise. Then, the observations were averaged in angular bins of different sizes, and the potential benefit of this process to reduce noise from the data was quantified. It was found that, if a 2° angular bin is used to average the data, the noise is reduced by up to 3 K. Furthermore, this method complements necessary data thinning approaches when a large volume of data is used in data assimilation systems.

Sub-millimeter wave radiometer for observation of cloud ice: a proposal for Japanese mission

Ice clouds play an important role in the energy budget of the atmosphere as well as in the hydrological cycle. Currently cloud ice is one of the largest remaining uncertainties in climate models. Large discrepancies arise from different assumptions on ice cloud properties, in particular on microphysics, which are not sufficiently constrained by measurements. Passive sub-millimeter wave (SMM) techniques have the potential of providing direct information on ice content and particle sizes with daily global coverage. Here we introduce a concept for a compact 2-receiver SMM sensor and demonstrate its capabilities on measurements of ice content, mean particle size, and cloud altitude.