scholarly journals Stepwise Assessment of Different Saltation Theories in Comparison with Field Observation Data

Atmosphere ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 10
Author(s):  
Haeju Lee ◽  
Sung Hoon Park
Keyword(s):  
Wind Erosion ◽  
Friction Velocity ◽  
Evaluation Studies ◽  
Surface Wind ◽  
Dust Emission ◽  
Measurement Data ◽  
Surface Wind Speed ◽  
Soil Conditions ◽  
Observation Data ◽  
Study Results

Wind-blown dust models use input data, including soil conditions and meteorology, to interpret the multi-step wind erosion process and predict the quantity of dust emission. Therefore, the accuracy of the wind-blown dust models is dependent on the accuracy of each input condition and the robustness of the model schemes for each elemental step of wind erosion. A thorough evaluation of a wind-blown model thus requires validation of the input conditions and the elemental model schemes. However, most model evaluations and intercomparisons have focused on the final output of the models, i.e., the vertical dust emission. Recently, a delicate set of measurement data for saltation flux and friction velocity was reported from the Japan-Australia Dust Experiment (JADE) Project, which enabled the step-by-step evaluation of wind-blown dust models up to the saltation step. When all the input parameters were provided from the observations, both the two widely used saltation schemes showed very good agreement with measurements, with the correlation coefficient and the agreement of index both being larger than 0.9, which demonstrated the strong robustness of the physical schemes for saltation. However, using the meteorology model to estimate the input conditions such as weather and soil conditions, considerably degraded the models’ performance. The critical reason for the model failure was determined to be the inaccuracy in the estimation of the threshold friction velocity (representing soil condition), followed by inaccurate estimation of surface wind speed. It was not possible to determine which of the two saltation schemes was superior, based on the present study results. Such differentiation will require further evaluation studies using more measurements of saltation flux and vertical dust emissions.

scholarly journals Anthropogenic Decline of African Dust inferred from Insights From the Holocene Records and Beyond: are dust purely  natural?

2021 ◽  
Author(s):  
Tianle Yuan ◽  
Hongbin Yu ◽  
Mian Chin ◽  
Lorraine Remer ◽  
David McGee ◽  
...  
Keyword(s):  
Surface Wind ◽  
Dust Emission ◽  
Surface Wind Speed ◽  
Natural Phenomenon ◽  
Unified Framework ◽  
Dust Source ◽  
The Holocene ◽  
African Dust ◽  
Source Regions ◽  
The Relationship

<p>African dust exhibits strong variability on a range of time scales. Here we show that the interhemispheric contrast in Atlantic SST (ICAS) drives African dust variability at decadal to millennial timescales, and the strong anthropogenic increase of the ICAS in the future will decrease African dust loading to a level never seen during the Holocene. We provide a physical framework to understand the relationship between the ICAS and African dust activity: positive ICAS anomalies push the Intertropical Convergence Zone (ITCZ) northward and decrease surface wind speed over African dust source regions, which reduces dust emission and transport. It provides a unified framework for and is consistent with relationships in the literature. We find strong observational and proxy‐record support for the ICAS‐ITCZ‐dust relationship during the past 160 and 17,000 years. Model‐projected anthropogenic increase of the ICAS will reduce African dust by as much as 60%, which has broad consequences. We posit that dust cannot be thought of as a purely natural phenomenon.</p>

scholarly journals The Temporal-Spatial Variations and Potential Causes of Dust Events in Xinjiang Basin During 1960–2015

2021 ◽  
Vol 9 ◽  
Author(s):  
Lamei Mu ◽  
Jing Su ◽  
Xinyue Mo ◽  
Nan Peng ◽  
Ying Xu ◽  
...  
Keyword(s):  
Wind Speed ◽  
Correlation Coefficient ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Spatial Variations ◽  
Observation Data ◽  
Active Period ◽  
Significant Downward Trend ◽  
Dust Events ◽  
Southern Xinjiang

Dust events not only cause local ecosystem degradation and desertification, but also have profound impacts on regional and global climate system, as well as air quality and human health. Dust events in Xinjiang Basin, as the important dust source of Eastern Asia, have undergone a significant change under the global warming background and may be in a new active period after 2000, which is worthy of study. This study provides the temporal and spatial variations of dust events in the Xinjiang Basin based on surface meteorological station observation data during 1960–2015. The results show that Southern Xinjiang is the main dust occurrence region where dust events are significantly more than that in the Northern Xinjiang, and each year more than 73% of dust events occurred in spring and summer. The dust index (DI), which is defined to represent the large-scale variation of dust event, shows a significant downward trend during the past 56 years with a linear decreasing rate −8.2 years−1 in Southern Xinjiang. The DI is positively correlated to surface wind speed with a mean correlation coefficient of 0.79. The declining trend of surface wind speed could explain dust events variation during 1960–2000. But in the new active period after 2000, the increase of DI is not consistent with the rising wind speed with the correlation coefficient decreasing to 0.34. It is found that, compared with 1960–1999, the average annual precipitation and frequency increased by 17.4 and 13% during 2000–2015, respectively, and the NDVI also increased at the same time, which indicates that the surface condition changes induced by the increase of precipitation might suppress the occurrence of dust. Moreover, the analysis of high-altitude wind field shows that the variation of the East Asian general circulation’s intensity, dominating the upper-level wind fields in the Xinjiang basin, will change the surface wind speed and precipitation, and further affect the occurrence of dust events.

scholarly journals How reliable are CMIP5 models in simulating dust optical depth?

2018 ◽  
Author(s):  
Bing Pu ◽  
Paul Ginoux
Keyword(s):  
Spatial Pattern ◽  
Optical Depth ◽  
North Africa ◽  
Regional Climate ◽  
Surface Wind ◽  
Dust Emission ◽  
Coupled Model ◽  
Northern China ◽  
Surface Wind Speed ◽  
Cmip5 Models

Abstract. Dust aerosol plays an important role in the climate system by affecting the radiative and energy balances. Biases in dust modeling may result in biases in simulating global energy budget and regional climate. It is thus very important to understand how well dust is simulated in the Coupled Model Intercomparison Project Phase 5 (CMIP5) models. Here seven CMIP5 models using interactive dust emission schemes are examined against satellite derived dust optical depth (DOD) during 2004–2016. It is found that multi-model mean can largely capture the global spatial pattern and zonal mean of DOD over land in present-day climatology in MAM and JJA. Global mean land DOD is underestimated by −25.2 % in MAM to −6.4 % in DJF. While seasonal cycle, magnitude, and spatial pattern are generally captured by multi-model mean over major dust source regions such as North Africa and the Middle East, these variables are not so well represented by most of the models in South Africa and Australia. Interannual variations of DOD are neither captured by most of the models nor by multi-model mean. Models also do not capture the observed connections between DOD and local controlling factors such as surface wind speed, bareness, and precipitation. The constraints from surface bareness are largely underestimated while the influences of surface wind and precipitation are overestimated. Projections of DOD change in the late half of the 21st century under the Representative Concentration Pathways 8.5 scenario by multi-model mean is compared with those projected by a regression model. Despite the uncertainties associated with both projections, results show some similarities between the two, e.g., DOD pattern over North Africa in DJF and JJA, an increase of DOD in the Arabian Peninsula in all seasons, and a decrease over northern China from MAM to SON.

scholarly journals Retrieving the global distribution of threshold of wind erosion from satellite data and implementing it into the GFDL AM4.0/LM4.0 model

2019 ◽  
Author(s):  
Bing Pu ◽  
Paul Ginoux ◽  
Huan Guo ◽  
N. Christine Hsu ◽  
John Kimball ◽  
...  
Keyword(s):  
Optical Depth ◽  
Seasonal Cycle ◽  
Wind Erosion ◽  
Surface Wind ◽  
Dust Emission ◽  
Global Distribution ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Threshold Velocity ◽  
Erosion Threshold ◽  
Dust Events

Abstract. Dust emission is initiated when surface wind velocities exceed the threshold of wind erosion. Most dust models used constant threshold values globally. Here we use satellite products to characterize the frequency of dust events and surface properties. By matching this frequency derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue aerosol products with surface winds, we are able to retrieve a climatological monthly global distribution of wind erosion threshold (Vthreshold) over dry and sparsely-vegetated surface. This monthly two-dimensional threshold velocity is then implemented into the Geophysical Fluid Dynamics Laboratory coupled land-atmosphere model (AM4.0/LM4.0). It is found that the climatology of dust optical depth (DOD) and total aerosol optical depth, surface PM10 dust concentrations, and seasonal cycle of DOD are better captured over the dust belt (i.e. North Africa and the Middle East) by simulations with the new wind erosion threshold than those using the default globally constant threshold. The most significant improvement is the frequency distribution of dust events, which is generally ignored in model evaluation. By using monthly rather than annual mean Vthreshold, all comparisons with observations are further improved. The monthly global threshold of wind erosion can be retrieved under different spatial resolutions to match the resolution of dust models and thus can help improve the simulations of dust climatology and seasonal cycle as well as dust forecasting.

scholarly journals Quantifying the impact of sub-grid surface wind variability on sea salt and dust emissions in CAM5

2015 ◽  
Vol 8 (8) ◽  
pp. 7249-7312
Author(s):  
K. Zhang ◽  
C. Zhao ◽  
H. Wan ◽  
Y. Qian ◽  
R. C. Easter ◽  
...  
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Dust Emission ◽  
Surface Wind Speed ◽  
Sea Salt ◽  
Dust Emissions ◽  
Wind Variability ◽  
Wind Events ◽  
The Impact ◽  
Meso Scale

Abstract. This paper evaluates the impact of sub-grid variability of surface wind on sea salt and dust emissions in the Community Atmosphere Model version 5 (CAM5). The basic strategy is to calculate emission fluxes multiple times, using different wind speed samples of a Weibull probability distribution derived from model-predicted grid-box mean quantities. In order to derive the Weibull distribution, the sub-grid standard deviation of surface wind speed is estimated by taking into account four mechanisms: turbulence under neutral and stable conditions, dry convective eddies, moist convective eddies over the ocean, and air motions induced by meso-scale systems and fine-scale topography over land. The contributions of turbulence and dry convective eddy are parameterized using schemes from the literature, while the wind variabilities caused by moist convective eddies and fine-scale topography are estimated using empirical relationships derived from an operational weather analysis dataset at 15 km resolution. The estimated sub-grid standard deviations of surface wind speed agree well with reference results derived from one year of global weather analysis at 15 km resolution and from two regional model simulations with 3 km grid spacing. The wind-distribution-based emission calculations are implemented in CAM5. Simulations at 2° resolution indicate that sub-grid wind variability has relatively small impacts (about 7 % increase) on the global annual mean emission of sea salt aerosols, but considerable influence on the emission of dust. Among the considered mechanisms, dry convective eddies and meso-scale flows associated with topography are major causes of dust emission enhancement. With all the four mechanisms included and without additional adjustment of uncertain parameters in the model, the simulated global and annual mean dust emission increase by about 50 % compared to the default model. By tuning the globally constant dust emission scale factor, the global annual mean dust emission, aerosol optical depth, and top-of-atmosphere radiative fluxes can be adjusted to the level of the default model, but the frequency distribution of dust emission changes, with more contribution from weaker wind events and less contribution from stronger wind events.

scholarly journals Impact of near-surface wind speed variability on wind erosion in the eastern agro-pastoral transitional zone of Northern China, 1982–2016

2019 ◽  
Vol 271 ◽  
pp. 102-115 ◽  
Author(s):  
Gangfeng Zhang ◽  
Cesar Azorin-Molina ◽  
Peijun Shi ◽  
Degen Lin ◽  
Jose A. Guijarro ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Erosion ◽  
Surface Wind ◽  
Northern China ◽  
Surface Wind Speed ◽  
Transitional Zone ◽  
Near Surface

scholarly journals Quantifying the impact of sub-grid surface wind variability on sea salt and dust emissions in CAM5

2016 ◽  
Vol 9 (2) ◽  
pp. 607-632 ◽  
Author(s):  
Kai Zhang ◽  
Chun Zhao ◽  
Hui Wan ◽  
Yun Qian ◽  
Richard C. Easter ◽  
...  
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Dust Emission ◽  
Surface Wind Speed ◽  
Sea Salt ◽  
Fine Scale ◽  
Dust Emissions ◽  
Wind Variability ◽  
Wind Events ◽  
The Impact

Abstract. This paper evaluates the impact of sub-grid variability of surface wind on sea salt and dust emissions in the Community Atmosphere Model version 5 (CAM5). The basic strategy is to calculate emission fluxes multiple times, using different wind speed samples of a Weibull probability distribution derived from model-predicted grid-box mean quantities. In order to derive the Weibull distribution, the sub-grid standard deviation of surface wind speed is estimated by taking into account four mechanisms: turbulence under neutral and stable conditions, dry convective eddies, moist convective eddies over the ocean, and air motions induced by mesoscale systems and fine-scale topography over land. The contributions of turbulence and dry convective eddy are parameterized using schemes from the literature. Wind variabilities caused by moist convective eddies and fine-scale topography are estimated using empirical relationships derived from an operational weather analysis data set at 15 km resolution. The estimated sub-grid standard deviations of surface wind speed agree well with reference results derived from 1 year of global weather analysis at 15 km resolution and from two regional model simulations with  3 km grid spacing.The wind-distribution-based emission calculations are implemented in CAM5. In terms of computational cost, the increase in total simulation time turns out to be less than 3 %. Simulations at 2° resolution indicate that sub-grid wind variability has relatively small impacts (about 7 % increase) on the global annual mean emission of sea salt aerosols, but considerable influence on the emission of dust. Among the considered mechanisms, dry convective eddies and mesoscale flows associated with topography are major causes of dust emission enhancement. With all the four mechanisms included and without additional adjustment of uncertain parameters in the model, the simulated global and annual mean dust emission increase by about 50 % compared to the default model. By tuning the globally constant dust emission scale factor, the global annual mean dust emission, aerosol optical depth, and top-of-atmosphere radiative fluxes can be adjusted to the level of the default model, but the frequency distribution of dust emission changes, with more contribution from weaker wind events and less contribution from stronger wind events. In Africa and Asia, the overall frequencies of occurrence of dust emissions increase, and the seasonal variations are enhanced, while the geographical patterns of the emission frequency show little change.

scholarly journals Forecast score distributions with imperfect observations

2021 ◽  
Vol 7 (2) ◽  
pp. 53-71
Author(s):  
Julie Bessac ◽  
Philippe Naveau
Keyword(s):  
Heavy Tails ◽  
Evaluation Studies ◽  
Surface Wind ◽  
Random Variable ◽  
Surface Wind Speed ◽  
Radar Data ◽  
Scoring Rules ◽  
Noise Model ◽  
Model Errors ◽  
Conditional Distributions

Abstract. The field of statistics has become one of the mathematical foundations in forecast evaluation studies, especially with regard to computing scoring rules. The classical paradigm of scoring rules is to discriminate between two different forecasts by comparing them with observations. The probability distribution of the observed record is assumed to be perfect as a verification benchmark. In practice, however, observations are almost always tainted by errors and uncertainties. These may be due to homogenization problems, instrumental deficiencies, the need for indirect reconstructions from other sources (e.g., radar data), model errors in gridded products like reanalysis, or any other data-recording issues. If the yardstick used to compare forecasts is imprecise, one can wonder whether such types of errors may or may not have a strong influence on decisions based on classical scoring rules. We propose a new scoring rule scheme in the context of models that incorporate errors of the verification data. We rely on existing scoring rules and incorporate uncertainty and error of the verification data through a hidden variable and the conditional expectation of scores when they are viewed as a random variable. The proposed scoring framework is applied to standard setups, mainly an additive Gaussian noise model and a multiplicative Gamma noise model. These classical examples provide known and tractable conditional distributions and, consequently, allow us to interpret explicit expressions of our score. By considering scores to be random variables, one can access the entire range of their distribution. In particular, we illustrate that the commonly used mean score can be a misleading representative of the distribution when the latter is highly skewed or has heavy tails. In a simulation study, through the power of a statistical test, we demonstrate the ability of the newly proposed score to better discriminate between forecasts when verification data are subject to uncertainty compared with the scores used in practice. We apply the benefit of accounting for the uncertainty of the verification data in the scoring procedure on a dataset of surface wind speed from measurements and numerical model outputs. Finally, we open some discussions on the use of this proposed scoring framework for non-explicit conditional distributions.

scholarly journals How reliable are CMIP5 models in simulating dust optical depth?

2018 ◽  
Vol 18 (16) ◽  
pp. 12491-12510 ◽  
Author(s):  
Bing Pu ◽  
Paul Ginoux
Keyword(s):  
Spatial Pattern ◽  
Optical Depth ◽  
North Africa ◽  
Regional Climate ◽  
Surface Wind ◽  
Dust Emission ◽  
Coupled Model ◽  
Northern China ◽  
Surface Wind Speed ◽  
Cmip5 Models

Abstract. Dust aerosol plays an important role in the climate system by affecting the radiative and energy balances. Biases in dust modeling may result in biases in simulating global energy budget and regional climate. It is thus very important to understand how well dust is simulated in the Coupled Model Intercomparison Project Phase 5 (CMIP5) models. Here seven CMIP5 models using interactive dust emission schemes are examined against satellite-derived dust optical depth (DOD) during 2004–2016. It is found that multi-model mean can largely capture the global spatial pattern and zonal mean of DOD over land in present-day climatology in MAM and JJA. Global mean land DOD is underestimated by −25.2 % in MAM to −6.4 % in DJF. While seasonal cycle, magnitude, and spatial pattern are generally captured by the multi-model mean over major dust source regions such as North Africa and the Middle East, these variables are not so well represented by most of the models in South Africa and Australia. Interannual variations in DOD are not captured by most of the models or by the multi-model mean. Models also do not capture the observed connections between DOD and local controlling factors such as surface wind speed, bareness, and precipitation. The constraints from surface bareness are largely underestimated while the influences of surface wind and precipitation are overestimated. Projections of DOD change in the late half of the 21st century under the Representative Concentration Pathways 8.5 scenario in which the multi-model mean is compared with that projected by a regression model. Despite the uncertainties associated with both projections, results show some similarities between the two, e.g., DOD pattern over North Africa in DJF and JJA, an increase in DOD in the central Arabian Peninsula in all seasons, and a decrease over northern China from MAM to SON.

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