No abstract

[1] The Indo-Gangetic (IG) plains is one of the largest and most densely populated regions in the world. Recent studies over the IG plains using multi-year (2000)(2001)(2002)(2003)(2004) satellite (including Moderate Resolution Imaging Spectroradiometer: MODIS) and ground Aerosol Robotic Network (AERONET) data show strong seasonal variability of aerosol optical depth (AOD) with maximum aerosol loading (>0.6-0.7 at 500 nm) during the pre-monsoon (summer) season. A number of major dust storms, originating from western arid and desert regions of Africa, Arabia and western part of India (Thar Desert), affect the whole IG plains during the pre-monsoon season (April-June). The mean AOD increases from 0.4-0.5 to more than 0.6-0.7 throughout the plains (>0.8-0.9 on the western side) as a result of the dust storm events. Pronounced changes in the aerosol optical parameters, derived from AERONET, have been observed over Kanpur (26.45°N, 80.35°E) during dust storm events (2001)(2002)(2003)(2004)(2005). The maximum AOD (at 500 nm) during dust event days show increase from $1 to $2.4 with advance of the pre-monsoon season (April-June). The aerosol size distribution (ASD) shows increase in radius from 1.71 to 2.24 mm (in coarse fraction) and decrease in the distribution width from 3.76 to 2.56 mm showing changes in the aerosol characteristics during dust events. The aerosol parameters [ASD, single scattering albedo (SSA, total and coarse mode) and real and imaginary parts of the refractive index] change significantly during dust events. The National Oceanic and Atmospheric Administration (NOAA) Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model (5-day back-trajectory) and MODIS level-3 daily data (AOD and Å ngström exponent) have been used to trace the source, path and spatial extent of dust storm events. During major dust events, enhancement of the total column water vapor is observed from MODIS level-3 daily water vapor data (near-infrared clear column) showing a strong association (72% correlation) with the AOD along the track of dust storms over the IG plains. A significant rise of 50-100% is observed in the ground level respirable suspended particulate matter (RSPM) concentration showing alarming health risks to the people living in the IG plains during dust storm events.Citation: Prasad, A. K., and R. P. Singh (2007), Changes in aerosol parameters during major dust storm events (2001 -2005) over the Indo-Gangetic Plains using AERONET and MODIS data,

No abstract

[1] Water vapor is an important and highly variable constituent in time and space; the knowledge of its variability is important in climate studies. In India, the ground observations of water vapor using conventional methods such as radiosonde are limited. In this paper, a comparison of hourly estimates of total column water vapor from Global Positioning System (GPS) with multisensor satellite is presented over three stations. We show quantitatively seasonal and monthly dependency of bias, standard deviation, root mean square error (RMSE), and the correlation coefficient between the water vapor data sets. The GPS and Aerosol Robotic Network (AERONET) water vapor show good agreement (R 2 = 95%, RMSE 3.87 mm, GPS-AERONET bias = À2.63 mm). On the basis of multiple-year data, Moderate Resolution Imaging Spectroradiometer near-infrared (MODIS NIR) clear column product shows higher correlation (R 2 = 89-93%) with GPS compared to infrared (IR) products (R 2 = 82-84%). MODIS is found to be overestimating in NIR clear and IR products in all seasons over India where the magnitude of bias and RMSE show systematic changes from month to month. MODIS is significantly underestimating in NIR cloudy column products during summer and monsoon seasons. MODIS NIR clear column (R 2 = 97%, RMSE 5.44 mm) and IR (R 2 = 81%, RMSE 7.17 mm) water vapor show similar performance on comparison with AERONET data. The MODIS NIR cloudy column product shows no correlation with GPS. The GPS National Centers for Environmental Prediction/Department of Energy Atmospheric Model Intercomparison Project II (GPS-NCEP/DOE AMIP-II) Reanalysis-2 water vapor show R 2 = 87%, 77%, and 60% (and RMSE of 8.39 mm, 6.97 mm, and 9.30 mm) over Kanpur, Hyderabad, and Bangalore, respectively. All the satellite water vapor shows systematic bias with month and season that is found to be sensitive to the sky conditions. The magnitude of bias is invariably larger during monsoon season with relatively more cloudy days and moist atmosphere. The errors in satellite estimation are found to be invariably more during wet compared to dry months. Statistical analysis shows that MODIS NIR clear column and Atmospheric Infrared Sounder (AIRS) daytime water vapor are more reliable compared to other satellite estimates (MODIS IR and AIRS nighttime) except during cloudy days.Citation: Prasad, A. K., and R. P. Singh (2009), Validation of MODIS Terra, AIRS, NCEP/DOE AMIP-II Reanalysis-2, and AERONET Sun photometer derived integrated precipitable water vapor using ground-based GPS receivers over India,

Abstract. Global warming or the increase of the surface and atmospheric temperatures of the Earth, is increasingly discernible in the polar, sub-polar and major land glacial areas. The Himalayan and Tibetan Plateau Glaciers, which are the largest glaciers outside of the Polar Regions, are showing a large-scale decrease of snow cover and an extensive glacial retreat. These glaciers such as Siachen and Gangotri are a major water resource for Asia as they feed major rivers such as the Indus, Ganga and Brahmaputra. Due to scarcity of ground measuring stations, the long-term observations of atmospheric temperatures acquired from the Microwave Sounding Unit (MSU) since 1979-2008 is highly useful. The lower and middle tropospheric temperature trend based on 30 years of MSU data shows warming of the Northern Hemisphere's midlatitude regions. The mean month-to-month warming (up to 0.048±0.026 • K/year or 1.44 • K over 30 years) of the mid troposphere (near surface over the high altitude Himalayas and Tibetan Plateau) is prominent and statistically significant at a 95% confidence interval. Though the mean annual warming trend over the Himalayas (0.016±0.005 • K/year), and Tibetan Plateau (0.008±0.006 • K/year) is positive, the month to month warming trend is higher (by 2-3 times, positive and significant) only over a period of six months (December to May). The factors responsible for the reversal of this trend from June to November are discussed here. The inequality in the magnitude of the warming trends of the troposphere between the western and easternCorrespondence to: A. K. Prasad (aprasad@chapman.edu) Himalayas and the IG (Indo-Gangetic) plains is attributed to the differences in increased aerosol loading (due to dust storms) over these regions. The monthly mean lowertropospheric MSU-derived temperature trend over the IG plains (dust sink region; up to 0.032±0.027 • K/year) and dust source regions (Sahara desert, Middle East, Arabian region, Afghanistan-Iran-Pakistan and Thar Desert regions; up to 0.068±0.033 • K/year) also shows a similar pattern of month-to-month oscillation and six months of enhanced and a statistically significant warming trend. The enhanced warming trend during the winter and pre-monsoon months (December-May) may accelerate glacial melt. The unequal distribution of the warming trend over the year is discussed in this study and is partially attributed to a number of controlling factors such as sunlight duration, CO 2 trends over the region (2003)(2004)(2005)(2006)(2007)(2008), water vapor and aerosol distribution.