Interannual variations in aerosol microstructure parameters according to data of sun photometer measurements in Tomsk

2017 ◽  
Vol 30 (6) ◽  
pp. 564-573
Author(s):  
V. V. Veretennikov
Keyword(s):  
Interannual Variations ◽  
Aerosol Microstructure ◽  
Microstructure Parameters ◽  
Sun Photometer

Soil Moisture Deficits in South-Central Sweden

1989 ◽  
Vol 20 (2) ◽  
pp. 109-122 ◽  
Author(s):  
Lotta Andersson
Keyword(s):  
Soil Moisture ◽  
Field Capacity ◽  
Interannual Variations ◽  
Neutron Probe ◽  
South Central ◽  
Normal Ranges ◽  
Moisture Fluxes ◽  
In The Beginning ◽  
Probe Measurements ◽  
Different Parts

Some commonly used assumptions about climatically induced soil moisture fluxes within years and between different parts of a region were challenged with the help of a conceptual soil moisture model. The model was optimised against neutron probe measurements from forest and grassland sites. Five 10 yrs and one 105 yrs long climatic records, from the province of Östergötland, situated in south-central Sweden, were used as driving variables. It was concluded that some of the tested assumptions should not be taken for granted. Among these were the beliefs that interannual variations of soil moisture contents can be neglected in the beginning of the hydrological year and that soils usually are filled up to field capacity after the autumn recharge. The calculated climatic induced dryness was estimated to be rather insensitive to the choice of climatic stations within the region. Monthly ranges of soil moisture deficits (1883-1987) were shown to be skewed and it is therefore recommended to use medians and standard deviations in statistical analyses of “normal” ranges of soil moisture deficits.

scholarly journals The Potential of GRASP/GARRLiC Retrievals for Dust Aerosol Model Evaluation: Case Study during the PreTECT Campaign

2021 ◽  
Vol 13 (5) ◽  
pp. 873
Author(s):  
Dimitra Konsta ◽  
Alexandra Tsekeri ◽  
Stavros Solomos ◽  
Nikolaos Siomos ◽  
Anna Gialitaki ◽  
...  
Keyword(s):  
Model Evaluation ◽  
Dust Concentration ◽  
Saharan Dust ◽  
North Coast ◽  
Concentration Profiles ◽  
Future Studies ◽  
Aerosol Model ◽  
The North ◽  
Sun Photometer

We use the Generalized Retrieval of Aerosol Surface Properties algorithm (GRASP) to compare with dust concentration profiles derived from the NMME-DREAM model for a specific dust episode. The GRASP algorithm provides the possibility of deriving columnar and vertically-resolved aerosol properties from a combination of lidar and sun-photometer observations. Herein, we apply GRASP for analysis of a Saharan dust outburst observed during the “PREparatory: does dust TriboElectrification affect our ClimaTe” campaign (PreTECT) that took place at the North coast of Crete, at the Finokalia ACTRIS station. GRASP provides column-averaged and vertically resolved microphysical and optical properties of the particles. The retrieved dust concentration profiles are compared with modeled concentration profiles derived from the NMME-DREAM dust model. To strengthen the results, we use dust concentration profiles from the POlarization-LIdar PHOtometer Networking method (POLIPHON). A strong underestimation of the maximum dust concentration is observed from the NMME-DREAM model. The reported differences between the retrievals and the model indicate a high potential of the GRASP algorithm for future studies of dust model evaluation.

scholarly journals Profiling Dust Mass Concentration in Northwest China Using a Joint Lidar and Sun-photometer Setting

2021 ◽  
Vol 13 (6) ◽  
pp. 1099
Author(s):  
Tianhe Wang ◽  
Ying Han ◽  
Wenli Hua ◽  
Jingyi Tang ◽  
Jianping Huang ◽  
...  
Keyword(s):  
Mass Concentration ◽  
Field Experiments ◽  
Negative Relationship ◽  
Northwest China ◽  
Dust Particles ◽  
Mass Loading ◽  
Average Mass ◽  
Dust Mass ◽  
Dust Loading ◽  
Sun Photometer

The satellite-based estimation of the dust mass concentration (DMC) is essential for accurately evaluating the global biogeochemical cycle of the dust aerosols. As for the uncertainties in estimating DMC caused by mixing dust and pollutants and assuming a fixed value for the mass extinction efficiency (MEE), a classic lidar-photometer method is employed to identify and separate the dust from pollutants, obtain the dust MEE, and evaluate the effect of the above uncertainties, during five dust field experiments in Northwest China. Our results show that this method is effective for continental aerosol mixtures consisting of dust and pollutants. It is also seen that the dust loading mainly occurred in the free troposphere (< 6 km), with the average mass loading of 905 ± 635 µg m−2 trapped in the planetary boundary layer. The dust MEE ranges from 0.30 to 0.60 m2 g−1 and has a significantly negative relationship with the size of dust particles. With the assumption of the dust MEE of 0.37 (0.60) m2 g−1, the DMC is shown to be overestimated (underestimated) by 20–40% (15–30%). In other words, our results suggest that the change of MEE with the size of dust particles should be considered in the estimation of DMC.

scholarly journals Retrieval of aerosol single-scattering albedo and polarized phase function from polarized sun-photometer measurements for Zanjan's atmosphere

2013 ◽  
Vol 6 (10) ◽  
pp. 2659-2669 ◽  
Author(s):  
A. Bayat ◽  
H. R. Khalesifard ◽  
A. Masoumi
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Atmospheric Aerosols ◽  
Phase Function ◽  
Single Scattering ◽  
Single Scattering Albedo ◽  
Angstrom Exponent ◽  
Ångström Exponent ◽  
Sun Photometer ◽  
Ångstrom Exponent

Abstract. The polarized phase function of atmospheric aerosols has been investigated for the atmosphere of Zanjan, a city in northwest Iran. To do this, aerosol optical depth, Ångström exponent, single-scattering albedo, and polarized phase function have been retrieved from the measurements of a Cimel CE 318-2 polarized sun-photometer from February 2010 to December 2012. The results show that the maximum value of aerosol polarized phase function as well as the polarized phase function retrieved for a specific scattering angle (i.e., 60°) are strongly correlated (R = 0.95 and 0.95, respectively) with the Ångström exponent. The latter has a meaningful variation with respect to the changes in the complex refractive index of the atmospheric aerosols. Furthermore the polarized phase function shows a moderate negative correlation with respect to the atmospheric aerosol optical depth and single-scattering albedo (R = −0.76 and −0.33, respectively). Therefore the polarized phase function can be regarded as a key parameter to characterize the atmospheric particles of the region – a populated city in the semi-arid area and surrounded by some dust sources of the Earth's dust belt.

Interannual Variations and Prediction of Spring Precipitation over China

2018 ◽  
Vol 31 (2) ◽  
pp. 655-670 ◽  
Author(s):  
YuJia You ◽  
Xiaojing Jia
Keyword(s):  
Regression Model ◽  
Yangtze River ◽  
Climate Models ◽  
Seasonal Forecast ◽  
Forecast Skill ◽  
Interannual Variations ◽  
The Yangtze River ◽  
Spring Precipitation ◽  
Coupled Climate Models ◽  
Time Variations

The interannual variations and the prediction of the leading two empirical orthogonal function (EOF) modes of spring (April–May) precipitation over China for the period from 1951 to 2014 are investigated using both observational data and the seasonal forecast made by six coupled climate models. The leading EOF mode of spring precipitation over China (EOF1-prec) features a monosign pattern, with the maximum loading located over southern China. The ENSO-related tropical Pacific SST anomalies in the previous winter can serve as a precursor for EOF1-prec. The second EOF mode of spring precipitation (EOF2-prec) over China is characterized by a dipole structure, with one pole near the Yangtze River and the other one with opposite sign over the Pearl River delta. A North Atlantic sea surface temperature (SST) anomaly dipole in the preceding March is found contribute to the prec-EOF2 and can serve as its predictor. A physics-based empirical (P-E) model is then formulated using the two precursors revealed by the observational analysis to forecast the variations of EOF1-prec and EOF2-prec. Compared to coupled climate models, which have little skill in forecasting the time variations of the two EOF modes, this P-E model can significantly improve the forecast skill of their time variations. A linear regression model is further established using the time series forecast by the P-E model to forecast the spring precipitation over China. Results suggest that the seasonal forecast skill of the spring precipitation over southeastern China, especially over the Yangtze River area, can be significantly improved by the regression model.

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