Special Issue "Remote Sensing in Climate Monitoring and Analysis"
A special issue of Remote Sensing (ISSN 2072-4292).
Deadline for manuscript submissions: closed (28 February 2011)
Dr. Richard Müller
German Meteorological Service CM-SAF, Frankfurter Straße 135, 63067 Offenbach, Germany
Phone: +49 (0) 69 8062 4922
Fax: +49 (0) 69 8062 4955
Interests: remote sensing of surface radiation; clouds and aerosols; sensor calibration; methods for \"merging\" in-situ data with remote sensing data
Climate monitoring and analysis is an important task in order to improve the understanding of climate dynamics and climate change. This in turn is a pre-requisite for reliable information bulletins on climate change and for the consultation of decision makers and end-users Remote Sensing is becoming more and more important for this issue for different reasons.
- Many regions in the world are characterized by the lack of a dense network of ground based measurements for ECVs.
- Some parameters can only be observed from space, or can be observed with a better accuracy from space (e.t top of atmosphere radiation budget)
- Remote Sensing provides climate variables with a large regional coverage up to global coverage.
- Assimilation of satellite data has largely increased the quality of reanalysis data.
- Satellite derived products have the potential to increase the accuracy of gridded climate data sets gained from dense ground based networks.
This special issue is dedicated to compile articles on:
- climate monitoring and analysis based on satellite derived essential climate variables.
- methods for the retrieval of Essential Climate Variables (ECVs) in climate quality.
- methods for the calibration and inter-calibration of satellite radiances.
- improvements of methods for the assimilation of satellite data within reanalysis.
- methods for data fusion of satellite based variables with reanalysis data and/or in-situ measurements.
- climate applications dealing with satellite based climate variables
Dr. Richard Müller
- radiative transfer
- water energy cycle
- retrieval of the radiation budget
- retrieval of aerosols and cloud properties
- calibration of satellite radiances
- retrieval of essential climate variables
- data assimilation
- data fusion