Fossil fuel combustion and fertilizer application in the United States have substantially altered the nitrogen cycle, with serious effects on climate change. The climate effects can be short-lived, by impacting the chemistry of the atmosphere, or long-lived, by altering ecosystem greenhouse gas fluxes. Here we develop a coherent framework for assessing the climate change impacts of US reactive nitrogen emissions, including oxides of nitrogen, ammonia, and nitrous oxide (N2O).

Methane (CH4) uptake by steppe soils is affected by a range of specific factors and is a complex process. Increased stocking rate promotes steppe degradation, with unclear consequences for gas exchanges. To assess the effects of grazing management on CH4 uptake in desert steppes, we investigated soil-atmosphere CH4 exchange during the winter-spring transition period.

South Asian emissions of fossil fuel SO2 and black carbon increased

Clouds and aerosol particles have bedevilled climate modellers for decades. Now researchers are starting to gain the upper hand.

Data from the satellite-based Special Sensor Microwave Imager (SSM/I) show that the total atmospheric moisture content over oceans has increased by 0.41 kg/m2 per decade since 1988. Results from current climate models indicate that water vapor increases of this magnitude cannot be explained by climate noise alone. In a formal detection and attribution analysis using the pooled results from 22 different climate models, the simulated “fingerprint” pattern of anthropogenically caused changes in water vapor is identifiable with high statistical confidence in the SSM/I data.

Climate models and satellite observations both indicate that the total amount of water in the atmosphere will increase at a rate of 7% per kelvin of surface warming. However, the climate models predict that global precipitation will increase at a much slower rate of 1 to 3% per kelvin. A recent analysis of satellite observations does not support this prediction of a muted response of precipitation to global warming. Rather, the observations suggest that precipitation and total atmospheric water have increased at about the same rate over the past two decades.

Human activities are releasing tiny particles (aerosols) into the atmosphere. These human-made aerosols enhance scattering and absorption of solar radiation. They also produce brighter clouds that are less efficient at releasing precipitation. These in turn lead to large reductions in the amount of solar irradiance reaching Earth's surface, a corresponding increase in solar heating of the atmosphere, changes in the atmospheric temperature structure, suppression of rainfall, and less efficient removal of pollutants.

India’s Cabinet has given its approval to a “National Monsoon Mission,” which will equip the weather department with high-end computers, radars and scientific manpower to generate more detailed and accurate forecasts.

India’s current antiquated methods of forecasting the all-important monsoon rains is getting a re-vamp.

No other weather phenomenon generates as much excitement among policymakers and economists, given that it holds the key to farm output, a sector employing half the country’s workforce.

Data on surface ozone concentration compiled for a 10-year period from 1990 to 1999 for Pune and Delhi are analyzed in terms of its frequency distribution, annual trend, diurnal variation and its relation with various meteorological and chemical parameters. It is found that the surface ozone concentration range showing highest frequency of occurrence at Pune is 0–5 ppb during winter and post-monsoon seasons and 15–20 ppb and 5–10 ppb during summer and monsoon seasons, respectively. It is 0–5 ppb at Delhi during all the seasons.

Regional Climate Model of version 3 (RegCM3) was driven with Emissions Scenarios A2 of ECHAM4 at 0.54°×0.54° horizontal grid resolution in two parameterizations: Grell scheme with Arakawa–Schubert (GAS) and Fritch–Chappell (GFC) assumptions. The simulated rainfall and mean surface air temperature were calibrated and validated against ground-based observed data in Bangladesh during the period 1961–1990. The Climate Research Unit (CRU) data is also used for understanding the model performance.

Pages