Elevated aerosol layer over South Asia worsens the Indian droughts.

Droughts have become more severe and recurrent over the Indian sub-continent during the second half of the twentieth century, leading to more severe hydro-climatic and socio-economic impacts over one of the most densely populated parts of the world. So far, droughts have mostly been connected to circulation changes concomitant with the abnormal warming over the Pacific Ocean, prevalently known as "El Niño". Here, exploiting observational data sets and a series of dedicated sensitivity experiments, we show that the severity of droughts during El Niño is amplified (17%) by changes in aerosols. The model experiments simulate the transport of boundary layer aerosols from South Asian countries to higher altitudes (12-18 km) where they form the Asian Tropopause Aerosol Layer (ATAL) (~ 60-120°E, 20-40°N). During El Niño, the anomalous overturning circulation from the East Asian region further enriches the thickness of aerosol layers in the ATAL over the northern part of South Asia. The anomalous aerosol loading in the ATAL reduces insolation over the monsoon region, thereby exacerbating the severity of drought by further weakening the monsoon circulation. Future increases in industrial emissions from both East and South Asia will lead to a wider and thicker elevated aerosol layer in the upper troposphere, potentially amplifying the severity of droughts.

Tropospheric ozone profiles from a ground-based ultraviolet spectrometer: a new retrieval method.

We present, to the best of our knowledge, a new method to retrieve tropospheric ozone (O3) profiles from ground-based ultraviolet spectroscopic measurements. This method utilizes radiance spectra in the Huggins bands (i.e., 300-340 nm) measured at three off-axis angles (e.g., 45 degrees, 75 degrees, and 85 degrees) normalized to direct-Sun irradiances or zenith-sky radiances with the total column O3 derived from direct-Sun or zenith-sky measurements as a constraint. The vertical resolution of the retrieved O3 values ranges from approximately 3 km near the surface to approximately 12 km at 20 km altitude. This method can be used to measure diurnal variation of tropospheric O3 profiles and is complementary to the Umkehr method that mainly measures ozone profiles in the stratosphere.

Mapping tropospheric ozone profiles from an airborne ultraviolet-visible spectrometer.

We present a novel technique for retrieving ozone (O3) profiles and especially tropospheric O3 from airborne UV/visible spectrometer measurements. This technique utilizes radiance spectra from one down-looking and two up-looking (85 degrees and 75 degrees) directions, taking advantage of the O3 absorption structure in the Huggins (300-340-nm) and Chappuis (530-650-nm) bands. This technique is especially sensitive to tropospheric O3 below and < or =8 km above the aircraft with a vertical resolution of 2-6 km and is sensitive to lower and middle stratospheric O3 with a vertical resolution of 8-15 km. It can measure tropospheric O3 at spatial resolutions of 2 km x 2 km or higher and is therefore well suited for regional air-quality studies and validation of satellite measurements.

Undersampling correction for array detector-based satellite spectrometers.

Array detector-based instruments are now fundamental to measurements of ozone and other atmospheric trace gases from space in the ultraviolet, visible, and infrared. The present generation of such instruments suffers, to a greater or lesser degree, from undersampling of the spectra, leading to difficulties in the analysis of atmospheric radiances. We provide extended analysis of the undersampling suffered by modern satellite spectrometers, which include the Global Ozone Monitoring Experiment, Scanning Imaging Absorption Spectrometer for Atmospheric Chartography, Ozone Monitoring Instrument, and Ozone Mapping and Profiler Suite. The analysis includes basic undersampling, the effects of binning into separate detector pixels, and the application of high-resolution Fraunhofer spectral data to correct for undersampling in many useful cases.