Shallow, maritime cumuli are ubiquitous over much of the tropical oceans, and characterizing their properties is important to understanding weather and climate. The Rain in Cumulus over the Ocean (RICO) field campaign, which took place during November 2004–January 2005 in the trades over the western Atlantic, emphasized measurements of processes related to the formation of rain in shallow cumuli, and how rain subsequently modifies the structure and ensemble statistics of trade wind clouds. Eight weeks of nearly continuous S-band polarimetric radar sampling, 57 flights from three heavily instrumented research aircraft, and a suite of ground- and ship-based instrumentation provided data on trade wind clouds with unprecedented resolution. Observational strategies employed during RICO capitalized on the advances in remote sensing and other instrumentation to provide insight into processes that span a range of scales and that lie at the heart of questions relating to the cause and effects of rain from shallow maritime cumuli.

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

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[1] We present the first detailed analysis of a 9 year (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008) seasonal climatology of size-and shape-segregated aerosol optical depth (AOD) and Ångström exponent (AE) over the Indian subcontinent derived from the Multiangle Imaging Spectroradiometer (MISR). Our analysis is evaluated against in situ observations to better understand the error characteristics of and to corroborate much of the space-time variability found within the MISR aerosol properties. The space-time variability is discussed in terms of aerosol sources, meteorology, and topography. We introduce indices based on aerosol size-and shapesegregated optical depth and their effect on AE that describe the relative seasonal change in anthropogenic and natural aerosols from the preceding season. Examples of major new findings include the following: (1) winter to premonsoon changes in aerosol properties are not just dominated by an increase in dust, as previously thought, but also by an increase in anthropogenic components, particularly in regions where biomass combustion is prevalent; (2) ∼15% of the AOD over the high wintertime pollution in the eastern IndoGangetic basin is due to large dust particles, resulting in the lowest AE (<0.8) over India in this season and likely caused by rural activities (e.g., agriculture, etc.) from the densely populated rural area; (3) while AOD decreases from the Indo-Gangetic basin up to the Tibetan Plateau, a large peak in AE and the fraction of AOD due to particle radii <0.7 mm exists in the foothills of the Himalayas, particularly in the premonsoon season; and (4) the AOD due to nonspherical particles exhibits a strong ocean-to-land gradient over all seasons because of topographical and meteorological controls.Citation: Dey, S., and L. Di Girolamo (2010), A climatology of aerosol optical and microphysical properties over the Indian subcontinent from 9 years

[1] This study presents a comprehensive statistical overview of the macrophysical properties of trade wind cumulus clouds over the tropical western Atlantic using 152 scenes taken from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) between September and December 2004. The size distribution, shapes, and spatial distribution of cumulus clouds were examined with ASTER nearinfrared data at 15 m resolution. The height distribution of these cumulus clouds was derived from ASTER thermal infrared data at 90 m resolution. The size distribution of cumuli exhibited a power law form and an exponent of 2.19 with a correlation coefficient of 0.99 using a direct power law fit method. The total cloud fraction of trade wind cumulus was 0.086, half of which was contributed from clouds smaller than 2 km in equivalent area diameter. An area-perimeter power law was observed with a dimension of 1.28 and a correlation coefficient of 0.87. The majority of cloudy pixels had cloud top altitudes around 1 km and increasing altitude with increasing cloud equivalent area diameter. Seventy-five percent of clouds have a nearest neighbor within a distance of 10 times their area-equivalent radius. Our results are compared to other studies of small cumulus taken over different parts of the world observed using different instruments. The statistics of cumuli observed in this study are poorly related to synoptic scale meteorological conditions from reanalysis data.Citation: Zhao, G., and L. Di Girolamo (2007), Statistics on the macrophysical properties of trade wind cumuli over the tropical western Atlantic,

[1] We present the first detailed spatial analysis of a fouryear, wintertime visible aerosol optical depth (AOD) c l i m a t o l o g y f r o m t h e M u l t i -a n g l e I m a g i n g SpectroRadiometer (MISR) over greater India. Meteorological fields from the National Centers for Environmental Prediction (NCEP) reanalysis, topographic data, and information related to aerosol source regions are used to explain the spatial patterns in MISR AODs. High AODs are found over much of greater India. The highest AODs are over the northern Indian state of Bihar, where we show that meteorology, topography, and aerosol sources all favor development of a concentrated pool of airborne particles. MISR AODs are validated against five groundbased sites in India and Nepal, revealing similar error characteristics found in other validation studies for the MISR aerosol product.

Exposures to ambient and household fine-particulate matter (PM2.5) together are among the largest single causes of premature mortality in India according to the Global Burden of Disease Studies (GBD). Several recent investigations have estimated that household emissions are the largest contributor to ambient PM2.5 exposure in the country. Using satellite-derived district-level PM2.5 exposure and an Eulerian photochemical dispersion model CAMx (Comprehensive Air Quality Model with Extensions), we estimate the benefit in terms of population exposure of mitigating household sources––biomass for cooking, space- and water-heating, and kerosene for lighting. Complete mitigation of emissions from only these household sources would reduce India-wide, population-weighted average annual ambient PM2.5 exposure by 17.5, 11.9, and 1.3%, respectively. Using GBD methods, this translates into reductions in Indian premature mortality of 6.6, 5.5, and 0.6%. If PM2.5 emissions from all household sources are completely mitigated, 103 (of 597) additional districts (187 million people) would meet the Indian annual air-quality standard (40 μg m−3) compared with baseline (2015) when 246 districts (398 million people) met the standard. At 38 μg m−3, after complete mitigation of household sources, compared with 55.1 μg m−3 at baseline, the mean annual national population-based concentration would meet the standard, although highly polluted areas, such as Delhi, would remain out of attainment. Our results support expansion of programs designed to promote clean household fuels and rural electrification to achieve improved air quality at regional scales, which also has substantial additional health benefits from directly reducing household air pollution exposures.

Precipitation characteristics of trade wind clouds over the Atlantic Ocean near Barbuda are derived from radar and aircraft data and are compared with satellite-observed cloud fields collected during the Rain in Cumulus over the Ocean (RICO) field campaign. S-band reflectivity measurements Z were converted to rainfall rates R using a Z-R relationship derived from aircraft measurements. Daily rainfall rates varied from 0 to 22 mm day 21 . The area-averaged rainfall rate for the 62-day period was 2.37 mm day 21 . If corrected for evaporation below cloud base, this value is reduced to 2.23 mm day 21 , which translates to a latent heat flux to the atmosphere of 63 W m 22 . When compared with the wintertime ocean-surface latent heat flux from this region, the average return of water to the ocean through precipitation processes within the trade wind layer during RICO was 31%-39%. A weak diurnal cycle was observed in the area-averaged rainfall rate. The magnitude of the rainfall and the frequency of its occurrence had a maximum in the predawn hours and a minimum in the midmorning to early afternoon on 64% of the days. Radar data were collocated with data from the Multiangle Imaging Spectroradiometer (MISR) to develop relationships between cloud-top height, cloud fraction, 866-nm bidirectional reflectance factor (BRF), and radar-derived precipitation. The collocation took place at the overpass time of ;1045 local time. These relationships revealed that between 5.5% and 10.5% of the cloudy area had rainfall rates that were . 0.1 mm h 21 , and between 1.5% and 3.5% of the cloudy area had rainfall rates that were .1 mm h 21 . Cloud-top heights between ;3 and 4 km and BRFs between 0.4 and 1.0 contributed ;50% of the total rainfall. For cloudy pixels having detectable rain, average rainfall rates increased from ;1 to 4 mm h 21 as cloud-top heights increased from ;1 to 4 km. Rainfall rates were closely tied to the type of mesoscale organization, with much of the rainfall originating from shallow (,5 km) cumulus clusters shaped as arcs associated with cold-pool outflows.