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Climate change has great significance in Asia in general, and India in particular; and atmospheric aerosols have a decisive role in this. The climate forcing potential of aerosols is closely linked to their optical, microphysical and chemical properties. Systematic efforts to characterize these properties over the Indian region started about 5 decades ago, and evolved over the years through concerted efforts in the form of long-term scientific programmes as well as concerted fields experiments. All these have resulted in this activity becoming one of the most vibrant fields of climate research in India and have brought several important issues in the national and international foci. The field experiment, RAWEX--GVAX (Regional Aerosol Warming Experiment--Ganges Valley Aerosol Experiment), conducted during 2011-12 jointly by the US Department of Energy, Indian Space Research Organization and Department of Science and Technology, has emerged as a direct outcome of the above efforts. This overview provides a comprehensive account of the development of aerosol--climate research in India and south Asia, and the accomplishment and newer issues that warranted the above field campaign. Details of RAWEX--GVAX, the major outcomes and the subsequent and more recent efforts are presented, followed by the way forward in this field for the next several years to come. [ABSTRACT FROM AUTHOR]

The radiosonde humidity profiles available during the Ganges Valley Experiment were compared to those simulated from the regional Weather Research and Forecasting (WRF) model coupled with a chemistry module (WRF-Chem) and the global reanalysis datasets. Large biases were revealed. On a monthly mean basis at Nainital, located in northern India, the WRF-Chem model simulates a large moist bias in the free troposphere (up to +20%) as well as a large dry bias in the boundary layer (up to -30%). While the overall pattern of the biases is similar, the magnitude of the biases varies from time to time and from one location to another. At Thiruvananthapuram, the magnitude of the dry bias is smaller, and in contrast to Nainital, the higher-resolution regional WRF-Chem model generates larger moist biases in the upper troposphere than the global reanalysis data. Furthermore, the humidity biases in the upper troposphere, while significant, have little impact on the model estimation of column aerosol optical depth (AOD). The frequent occurrences of the dry boundary-layer bias simulated by the large-scale models tend to lead to the underestimation of AOD. It is thus important to quantify the humidity vertical profiles for aerosol simulations over South Asia. [ABSTRACT FROM AUTHOR]

An introduction to a series of articles about the regional aerosol warming experiment - Ganges Valley aerosol experiment (RAWEX-GVAX) published within the issue is presented.

An extensive field study, RAWEX--GVAX, was carried out during a 10-month (June 2011-March 2012) campaign at ARIES, Nainital and observations on a wide range of parameters like physical and optical properties of aerosols, meteorological parameters and boundary layer evolution were made. This work presents results obtained from high-frequency (four launches per day), balloon-borne observations of meteorological parameters (pressure, temperature, relative humidity, wind speed and wind direction). These observations show wind speed as high as 84 m/s near the subtropical jet. It is shown that reanalysis wind speeds are in better agreement at 250 hPa (altitude of subtropical jet) than those above or below this value (100 hPa or 500 hPa). These observations also demonstrate that AIRS-derived temperature profiles are negatively biased in the lower altitude region, whereas they are positively biased near the tropopause. WRF simulated results are able to capture variations in temperature, humidity and wind speed profile reasonable well. WRF and AIRS-derived tropopause height, tropopause pressure and tropopause temperature also show agreement with radiosonde estimates. [ABSTRACT FROM AUTHOR]

We present the measurements of cloud-base height variations over Aryabhatta Research Institute of Observational Science, Nainital (79.45°E, 29.37°N, 1958 m amsl) obtained from Vaisala Ceilometer, during the nearly year-long Ganges Valley Aerosol Experiment (GVAX). The cloud-base measurements are analysed in conjunction with collocated measurements of rainfall, to study the possible contributions from different cloud types to the observed monsoonal rainfall during June to September 2011. The summer monsoon of 2011 was a normal monsoon year with total accumulated rainfall of 1035.8 mm during June-September with a maximum during July (367.0 mm) and minimum during September (222.3 mm). The annual mean monsoon rainfall over Nainital is 1440 ± 430 mm. The total rainfall measured during other months (October 2011-March 2012) was only 9% of that observed during the summer monsoon. The first cloud-base height varied from about 31 m above ground level (AGL) to a maximum of 7.6 km AGL during the summer monsoon period of 2011. It is found that about 70% of the total rain is observed only when the first cloud-base height varies between surface and 2 km AGL, indicating that most of the rainfall at high altitude stations such as Nainital is associated with stratiform low-level clouds. However, about 25% of the total rainfall is being contributed by clouds between 2 and 6 km. The occurrences of high-altitude cumulus clouds are observed to be only 2-4%. This study is an attempt to fill a major gap of measurements over the topographically complex and observationally sparse northern Indian region providing the evaluation data for atmospheric models and therefore, have implications towards the better predictions of monsoon rainfall and the weather components over this region. [ABSTRACT FROM AUTHOR]

The RAWEX-GVAX field campaign has been carried out from June 2011 to March 2012 over a high altitude site Manora Peak, Nainital (29.4°N; 79.2°E; 1958 m amsl) in the central Himalayas to assess the impacts of absorbing aerosols on atmospheric thermodynamics and clouds. This paper presents the preliminary results of the observations and data analysis of the Doppler Lidar, installed at Nainital. Strong updrafts with vertical winds in the range of ~2-4 ms-1 occurred during the daytime and throughout the season indicating thermally driven convection. On the other hand during nighttime, weak downdrafts persisted during stable conditions. Plan Position Indicator scan of Doppler Lidar showed north-northwesterly winds in the boundary layer. The mixing layer height, derived from the vertical velocity variance, showed diurnal variations, in the range ~0.7-1 km above ground level during daytime and very shallow during nighttime. [ABSTRACT FROM AUTHOR]

We present the measurement of cloud base height (CBH) derived from the Doppler Lidar (DL), Ceilometer (CM) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite over a high altitude station in the central Himalayan region for the first time. We analyzed six cases of cloud overpass during the daytime convection period by using the cloud images captured by total sky imager. The occurrence of thick clouds (> 50%) over the site is more frequent than thin clouds (< 40%). In every case, the CBH indicates less than 1.2 km, above ground level (AGL) observed by both DL and CM instruments. The presence of low level clouds in the height-time variation of signal to noise ratio of DL and backscatter of CM shows a similar diurnal pattern on all days. Cloud fraction is found to be maximum during the convective period. The CBH estimated by the DL and CM showed reasonably good correlation (R² = 0.76). The DL observed updraft fraction and cloud base vertical velocity also shows good correlation (R² = 0.66). The inter-comparison between DL and CM will have implications in filling the gap of CBH measurements by the DL, in absence of CM. More deployments of such instruments will be invaluable for the validations of meteorological models over the observationally sparse Indian regions. [ABSTRACT FROM AUTHOR]

The aerosol mass concentrations over several Indian regions have been simulated using the online chemistry transport model, WRF-Chem, for two distinct seasons of 2011, representing the pre-monsoon (May) and post-monsoon (October) periods during the Indo-US joint experiment 'Ganges Valley Aerosol Experiment (GVAX)'. The simulated values were compared with concurrent measurements. It is found that the model systematically underestimates near-surface BC mass concentrations as well as columnar Aerosol Optical Depths (AODs) from the measurements. Examining this in the light of the modelsimulated meteorological parameters, we notice the model overestimates both planetary boundary layer height (PBLH) and surface wind speeds, leading to deeper mixing and dispersion and hence lower surface concentrations of aerosols. Shortcoming in simulating rainfall pattern also has an impact through the scavenging effect. It also appears that the columnar AODs are influenced by the unrealistic emission scenarios in the model. Comparison with vertical profiles of BC obtained from aircraft-based measurements also shows a systematic underestimation by the model at all levels. It is seen that concentration of other aerosols, viz., dust and sea-salt are closely linked with meteorological conditions prevailing over the region. Dust is higher during pre-monsoon periods due to the prevalence of north-westerly winds that advect dust from deserts of west Asia into the Indo-Gangetic plain. Winds and rainfall influence sea-salt concentrations. Thus, the unrealistic simulation of wind and rainfall leads to model simulated dust and sea-salt also to deviate from the real values; which together with BC also causes underperformance of the model with regard to columnar AOD. It appears that for better simulations of aerosols over Indian region, the model needs an improvement in the simulation of the meteorology. [ABSTRACT FROM AUTHOR]

The potential impact of climate change on agriculture is uncertain. In addition, agriculture could influence above-and below-ground carbon storage. Development of models that represent agriculture is necessary to address these impacts. We have developed an approach to integrate agriculture representations for three crop types - maize, soybean, and spring wheat - into the coupled carbon-nitrogen version of the Community Land Model (CLM), to help address these questions. Here we present the new model, CLMCrop, validated against observations from two AmeriFlux sites in the United States, planted with maize and soybean. Seasonal carbon fluxes compared well with field measurements for soybean, but not as well for maize. CLM-Crop yields were comparable with observations in countries such as the United States, Argentina, and China, although the generality of the crop model and its lack of technology and irrigation made direct comparison difficult. CLM-Crop was compared against the standard CLM3.5, which simulates crops as grass. The comparison showed improvement in gross primary productivity in regions where crops are the dominant vegetation cover. Crop yields and productivity were negatively correlated with temperature and positively correlated with precipitation, in agreement with other modeling studies. In case studies with the new crop model looking at impacts of residue management and planting date on crop yield, we found that increased residue returned to the litter pool increased crop yield, while reduced residue returns resulted in yield decreases. Using climate controls to signal planting date caused different responses in different crops. Maize and soybean had opposite reactions: when low temperature threshold resulted in early planting, maize responded with a loss of yield, but soybean yields increased. Our improvements in CLM demonstrate a new capability in the model - simulating agriculture in a realistic way, complete with fertilizer and residue management practices. Results are encouraging, with improved representation of human influences on the land surface and the potentially resulting climate impacts. [ABSTRACT FROM AUTHOR]

The article presents information on a study conducted on the impact of climate change on agriculture. In the study, Community Land Model (CLM)-Crop was validated against observations from two agricultural sites in the U.S., that were planted with maize and soybean. CLM-Crop was compared with the standard CLM3.5, which is associated with crops as grass. The study found that crop yields and productivity had a negative correlation with temperature, and a positive correlation with precipitation.