Clouds cover about 70% of the Earth's surface and playa dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the whole globe and across the wide range of spatial and temporal scales that comprise weather and climate variability. Satellite cloud data records now exceed more than 25 years in length. However, climatologies compiled from different satellite datasets can exhibit systematic biases. Questions therefore arise as to the accuracy and Capsule:Cloud properties derived from space observations are immensely valuable for climate studies and model evaluati~n; this assessment has revealed how their statistics may be affected by instrument capabilities and/or retrieval methods but also highlight those well determined.2

[1] A 22-year survey of tropical convection penetrating into the stratosphere has been conducted using special subsets of the International Satellite Cloud Climatology Project cloud data set. In addition to refined information about the geographic distribution of penetrating convective systems, these results show that penetrating convection occurs predominantly in the larger, organized, mesoscale convective systems, whereas smaller, unorganized convective systems rarely penetrate. Durations of penetrating events are longest for the largest systems, hurricanes and typhoons, generally exceeding one day.

Classifying tropical deep convective systems by the mesoscale distribution of their cloud properties and sorting matching precipitation measurements over an 11-yr period reveals that the whole distribution of instantaneous precipitation intensity and daily average accumulation rate is composed of (at least) two separate distributions representing distinctly different types of deep convection associated with different meteorological conditions (the distributions of non-deep-convective situations are also shown for completeness). The two types of deep convection produce very different precipitation intensities and occur with very different frequencies of occurrence. Several previous studies have shown that the interaction of the largescale tropical circulation with deep convection causes switching between these two types, leading to a substantial increase of precipitation. In particular, the extreme portion of the tropical precipitation intensity distribution, above 2 mm h 21, is produced by 40% of the larger, longer-lived mesoscale-organized type of convection with only about 10% of the ordinary convection occurrences producing such intensities. When average precipitation accumulation rates are considered, essentially all of the values above 2 mm h 21 are produced by the mesoscale systems. Yet today's atmospheric models do not represent mesoscale-organized deep convective systems that are generally larger than current-day circulation model grid cell sizes but smaller than the resolved dynamical scales and last longer than the typical physics time steps. Thus, model-based arguments for how the extreme part of the tropical precipitation distribution might change in a warming climate are suspect.

[1] The polarized scattering signatures observed in convective cloud systems with the Tropical Rainfall Measuring Mission (TRMM) Microwave Instrument are analyzed. In particular, and in contrast to the positive polarization difference (TbV-TbH > 0) observed when scattering by large ice particles is important, we also find a negative polarization difference. Radiative transfer simulations show that such a polarization difference can be explained by relatively large, mostly vertically oriented, nonspherical particles but not by horizontally or randomly oriented non-spherical particles. We establish a relationship between the occurrence of the negative polarization difference signature and electrical activity in the cloud using coincident observations by the Lightning Imaging Sensor also on board TRMM. The negative polarization difference is thus related to non-spherical particles that are mostly vertically oriented as revealed by the lightning activity. This result confirms that a careful analysis of passive microwave observations over clouds provides valuable information about the cloud ice phase. Citation: Prigent, C.,

Abstract. Microwave observations at low frequencies exhibit more sensitivity to surface and subsurface properties with little interference from the atmosphere. The objective of this study is to develop a global land emissivity product using passive microwave observations from the Advanced Microwave Scanning Radiometer -Earth Observing System (AMSR-E) and to investigate its sensitivity to land surface properties. The developed product complements existing land emissivity products from SSM/I and AMSU by adding land emissivity estimates at two lower frequencies, 6.9 and 10.65 GHz (C-and X-band, respectively). Observations at these low frequencies penetrate deeper into the soil layer. Ancillary data used in the analysis, such as surface skin temperature and cloud mask, are obtained from International Satellite Cloud Climatology Project (ISCCP). Atmospheric properties are obtained from the TIROS Operational Vertical Sounder (TOVS) observations to determine the small upwelling and downwelling atmospheric emissions as well as the atmospheric transmission. A sensitivity test confirms the small effect of the atmosphere but shows that skin temperature accuracy can significantly affect emissivity estimates. Retrieved emissivities at C-and X-bands and their polarization differences exhibit similar patterns of variation with changes in land cover type, soil moisture, and vegetation density as seen at SSM/I-like frequencies (Ka and Ku bands). The emissivity maps from AMSR-E at these higher frequencies agree reasonably well with the existing SSM/I-based product. The inherent discrepancy introduced by the difference between SSM/I and AMSR-E frequencies, incidence angles, and calibration has been assessed. SigCorrespondence to: H. Norouzi (hnorouzi@citytech.cuny.edu) nificantly greater standard deviation of estimated emissivities compared to SSM/I land emissivity product was found over desert regions. Large differences between emissivity estimates from ascending and descending overpasses were found at lower frequencies due to the inconsistency between thermal IR skin temperatures and passive microwave brightness temperatures which can originate from below the surface. The mismatch between day and night AMSR-E emissivities is greater than ascending and descending differences of SSM/I emissivity. This is because of unique orbit time of AMSR-E (01:30 a.m./p.m. LT) while other microwave sensors have orbit time of 06:00 to 09:00 (a.m./p.m.). This highlights the importance of considering the penetration depth of the microwave signal and diurnal variability of the temperature in emissivity retrieval. The effect of these factors is greater for AMSR-E observations than SSM/I observations, as AMSR-E observations exhibit a greater difference between day and night measures. This issue must be addressed in future studies to improve the accuracy of the emissivity estimates especially at AMSR-E lower frequencies.