PARAGON - An integrated approach for characterizing aerosol climate impacts and environmental interactions

Aerosols exert myriad influences on the earth's environment and climate, and on human health. The complexity of aerosol-related processes requires that information gathered to improve our understanding of climate change must originate from multiple sources, and that effective strategies for data integration need to be established. While a vast array of observed and modeled data are becoming available, the aerosol research community currently lacks the necessary tools and infrastructure to reap maximum scientific benefit from these data. Spatial and temporal sampling differences among a diverse set of sensors, nonuniform data qualities, aerosol mesoscale variabilities, and difficulties in separating cloud effects are some of the challenges that need to be addressed. Maximizing the long-term benefit from these data also requires maintaining consistently well-understood accuracies as measurement approaches evolve and improve. Achieving a comprehensive understanding of how aerosol physical, chemical, and radiative processes impact the earth system can be achieved only through a multidisciplinary, inter-agency, and international initiative capable of dealing with these issues. A systematic approach, capitalizing on modern measurement and modeling techniques, geospatial statistics methodologies, and high-performance information technologies, can provide the necessary machinery to support this objective. We outline a framework for integrating and interpreting observations and models, and establishing an accurate, consistent, and cohesive long-term record, following a strategy whereby information and tools of progressively greater sophistication are incorporated as problems of increasing complexity are tackled. This concept is named the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON). To encompass the breadth of the effort required, we present a set of recommendations dealing with data interoperability; measurement and model integration; multisensor synergy; data summarization and mining; model evaluation; calibration and validation; augmentation of surface and in situ measurements; advances in passive and active remote sensing; and design of satellite missions. Without an initiative of this nature, the scientific and policy communities will continue to struggle with understanding the quantitative impact of complex aerosol processes on regional and global climate change and air qualit

Study on retrieval algorithms for a backscatter lidar - Final report

In this study a systematic approach is used to find the most suitable algorithm for the inversion of space borne backscatter lidar signals. First a review of existing lidar algorithms is presented. The widely used analytical inversion method appeared to be the most promising one. For this algorithm a detailed error analysis is performed including propagation of all rel— evant systematic and statistical errors. Computer code is developed and tested using synthetic data as well as experimental ones. All tests proved the code to work well. For general use it is recommended to use the analytical inversion algorithm in the forward integration mode in conjunction with absolute calibration of the lidar signals. In special situations better stability can be achieved by using the backward integration mode, provided that suitable calibration targets at the far end of the lidar measurement range can be found. It is recommended to initiate a systematic investigation of objects in the atmosphere and at the surface which could be used as calibration targets. Additionally, further investigations should be performed concerning a modi— fied inverse modeling approach. This algorithm appears to have a high potential for avoiding some of the instabilities due to the rather large noise contribution to the expected ATLID signals

Bragg ptychography imaging of phase-ordering Fe-Al alloys

International audienc