Aerosol-cloud interactions remain a major uncertainty in climate research. Studies have indicated that model estimates of cloud susceptibility to aerosols frequently exceed satellite estimates, motivating model reformulations to increase agreement. Here we show that conventional ways of using satellite information to estimate susceptibility can serve as only a weak constraint on models because the estimation is sensitive to errors in the retrieval procedures.

Human activities have been implicated in the observed increase in Global Mean Surface Temperature. Over regional scales where climatic changes determine societal impacts and drive adaptation related decisions, detection and attribution (D&A) of climate change can be challenging due to the greater contribution of internal variability, greater uncertainty in regionally important forcings, greater errors in climate models, and larger observational uncertainty in many regions of the world.

A new comprehensive surface temperature data set for India is used to document changes in Indian temperature over seven decades, in order to examine the patterns and possible effects of global warming. The data set is subdivided into pre-monsoon, monsoon, and post-monsoon categories in order to study the temperature patterns in each of these periods.

Deposition and accumulation of light-absorbing carbonaceous aerosol on glacier surfaces can alter the energy balance of glaciers. In this study, 2 years (December 2014 to December 2016) of continuous observations of carbonaceous aerosols in the glacierized region of the Mt. Yulong and Ganhaizi (GHZ) basin are analyzed. The average elemental carbon (EC) and organic carbon (OC) concentrations were 1.51±0.93 and 2.57±1.32 µg m−3, respectively.

This study details the capabilities of the IITM Earth System Model version 2 (IITM‐ESMv2), developed at the Indian Institute of Tropical Meteorology, Pune, India, for investigating long‐term climate variability and change with special focus on the South Asian monsoon.

Original Source

Aerosol Optical Thickness (AOT) is a measure of solar spectral extinction. Long term AOT data analysis gives a picture of air quality for that location. This type of analysis is useful in the study of impact of urbanization on local climate. Aerosols are one of the most important but poorly understood factors that influence global climate change (IPCC, 2001). This calls for a need to regularly monitor the global aerosol distributions and study how they are changing over time.

A very unusual dust plume generated from dust-storm activities over the Arabian Peninsula and Southwest Asia affected the north-west region of India between March 20 and 23, 2012, causing significant reductions in air quality and consequently changes in meteorological parameters. Ground based measurements of aerosol optical depth at 500 nm reached 1.015 ± 0.24 and 0.837 ± 0.042 at Jodhpur while Angstrom exponent dropped to -0.030 and -0.065 on March 20 and 21, 2012 respectively. The AOD reached 0.959 in Delhi while Angstrom exponent dropped to 0.006 on March 21, 2012.

Since at least the 1980s, many farmers in northwest India have switched to mechanized combine harvesting to boost efficiency. This harvesting technique leaves abundant crop residue on the fields, which farmers typically burn to prepare their fields for subsequent planting. A key question is to what extent the large quantity of smoke emitted by these fires contributes to the already severe pollution in Delhi and across other parts of the heavily populated Indo-Gangetic Plain located downwind of the fires.

Aerosols play an important role in climate change processes. Among the various aerosols, black carbon (BC) has been recognized as the second most important anthropogenic agent for climate change and the primary tracer for adverse health effects caused by air pollution. The increasing concentration of BC in the atmosphere has now become a matter of serious concern, especially in the high Himalayan glaciated region that has the most vulnerable ecosystem with pristine environment, rich biodiversity and pollution-free ambient air quality.

Albedo—a primary control on surface melt—varies considerably across the Greenland Ice Sheet yet the specific surface types that comprise its dark zone remain unquantified. Here we use UAV imagery to attribute seven distinct surface types to observed albedo along a 25 km transect dissecting the western, ablating sector of the ice sheet. Our results demonstrate that distributed surface impurities—an admixture of dust, black carbon and pigmented algae—explain 73% of the observed spatial variability in albedo and are responsible for the dark zone itself.