scholarly journals The AFWA dust emission scheme for the GOCART aerosol model in WRF-Chem v3.8.1

2021 ◽  
Author(s):  
Sandra LeGrand ◽  
Christopher Polashenski ◽  
Theodore Letcher ◽  
Glenn Creighton ◽  
Steven Peckham ◽  
...  
Keyword(s):  
Dust Emission ◽  
Model Performance ◽  
The Other ◽  
Dust Particles ◽  
Aerosol Model ◽  
Weather Modeling ◽  
Institute Of Technology ◽  
Earth’S Climate ◽  
Improved Model ◽  
Gocart Model

Airborne particles of mineral dust play a key role in Earth’s climate system and affect human activities around the globe. The numerical weather modeling community has undertaken considerable efforts to accurately forecast these dust emissions. Here, for the first time in the literature, we thoroughly describe and document the Air Force Weather Agency (AFWA) dust emission scheme for the Georgia Institute of Technology–Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) aerosol model within the Weather Research and Forecasting model with chemistry (WRF-Chem) and compare it to the other dust emission schemes available in WRF-Chem. The AFWA dust emission scheme addresses some shortcomings experienced by the earlier GOCART-WRF scheme. Improved model physics are designed to better handle emission of fine dust particles by representing saltation bombardment. WRF-Chem model performance with the AFWA scheme is evaluated against observations of dust emission in southwest Asia and compared to emissions predicted by the other schemes built into the WRF-Chem GOCART model. Results highlight the relative strengths of the available schemes, indicate the reasons for disagreement, and demonstrate the need for improved soil source data.

scholarly journals The AFWA dust emission scheme for the GOCART aerosol model in WRF-Chem v3.8.1

2019 ◽  
Vol 12 (1) ◽  
pp. 131-166 ◽  
Author(s):  
Sandra L. LeGrand ◽  
Chris Polashenski ◽  
Theodore W. Letcher ◽  
Glenn A. Creighton ◽  
Steven E. Peckham ◽  
...  
Keyword(s):  
Dust Emission ◽  
Model Performance ◽  
The Other ◽  
Dust Particles ◽  
Aerosol Model ◽  
Weather Modeling ◽  
Institute Of Technology ◽  
Earth’S Climate ◽  
Improved Model ◽  
Gocart Model

Abstract. Airborne particles of mineral dust play a key role in Earth's climate system and affect human activities around the globe. The numerical weather modeling community has undertaken considerable efforts to accurately forecast these dust emissions. Here, for the first time in the literature, we thoroughly describe and document the Air Force Weather Agency (AFWA) dust emission scheme for the Georgia Institute of Technology–Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) aerosol model within the Weather Research and Forecasting model with chemistry (WRF-Chem) and compare it to the other dust emission schemes available in WRF-Chem. The AFWA dust emission scheme addresses some shortcomings experienced by the earlier GOCART-WRF scheme. Improved model physics are designed to better handle emission of fine dust particles by representing saltation bombardment. WRF-Chem model performance with the AFWA scheme is evaluated against observations of dust emission in southwest Asia and compared to emissions predicted by the other schemes built into the WRF-Chem GOCART model. Results highlight the relative strengths of the available schemes, indicate the reasons for disagreement, and demonstrate the need for improved soil source data.

scholarly journals The AFWA Dust Emissions Scheme for the GOCART Aerosol Model in WRF-Chem

2018 ◽  
Author(s):  
Sandra L. LeGrand ◽  
Chris Polashenski ◽  
Theodore W. Letcher ◽  
Glenn A. Creighton ◽  
Steven E. Peckham ◽  
...  
Keyword(s):  
Dust Emission ◽  
Model Performance ◽  
The Other ◽  
Dust Particles ◽  
Dust Emissions ◽  
Aerosol Model ◽  
Weather Modeling ◽  
Earth’S Climate ◽  
Improved Model ◽  
Gocart Model

Abstract. Airborne particles of mineral dust play a key role in Earth's climate system and affect human activities around the globe. The numerical weather modeling community has undertaken considerable efforts to accurately forecast these dust emissions. Here, for the first time in the literature, we thoroughly describe and document the Air Force Weather Agency (AFWA) dust emission scheme for the GOCART aerosol model within the Weather Research and Forecasting Chemistry (WRF-Chem) model and compare it to the other dust emission parameterizations available in WRF-Chem. The AFWA dust emission scheme addresses some shortcomings experienced by the earlier GOCART-WRF parameterization. Improved model physics are designed to better handle emission of fine dust particles by representing saltation bombardment. Model performance with the improved parameterization is evaluated against observations of dust emission in southwest Asia and compared to emissions predicted by the other parameterizations built into the WRF-Chem GOCART model. Results highlight the relative strengths of the available schemes, indicate the reasons for disagreement between the models, and demonstrate the need for improved soil source data.

scholarly journals Sensitivity of the WRF-Chem (V3.6.1) model to different dust emission parametrisation: assessment in the broader Mediterranean region

2017 ◽  
Vol 10 (8) ◽  
pp. 2925-2945 ◽  
Author(s):  
Emmanouil Flaounas ◽  
Vassiliki Kotroni ◽  
Konstantinos Lagouvardos ◽  
Martina Klose ◽  
Cyrille Flamant ◽  
...  
Keyword(s):  
North Africa ◽  
Eastern Mediterranean ◽  
Dust Emission ◽  
Model Performance ◽  
Dust Particles ◽  
Dust Transport ◽  
Dust Emissions ◽  
Extinction Coefficients ◽  
Airborne Measurements ◽  
Model Aerosol

Abstract. In this study we aim to assess the WRF-Chem model capacity to reproduce dust transport over the eastern Mediterranean. For this reason, we compare the model aerosol optical depth (AOD) outputs to observations, focusing on three key regions: North Africa, the Arabian Peninsula and the eastern Mediterranean. Three sets of four simulations have been performed for the 6-month period of spring and summer 2011. Each simulation set uses a different dust emission parametrisation and for each parametrisation, the dust emissions are multiplied with various coefficients in order to tune the model performance. Our assessment approach is performed across different spatial and temporal scales using AOD observations from satellites and ground-based stations, as well as from airborne measurements of aerosol extinction coefficients over the Sahara. Assessment over the entire domain and simulation period shows that the model presents temporal and spatial variability similar to observed AODs, regardless of the applied dust emission parametrisation. On the other hand, when focusing on specific regions, the model skill varies significantly. Tuning the model performance by applying a coefficient to dust emissions may reduce the model AOD bias over a region, but may increase it in other regions. In particular, the model was shown to realistically reproduce the major dust transport events over the eastern Mediterranean, but failed to capture the regional background AOD. Further comparison of the model simulations to airborne measurements of vertical profiles of extinction coefficients over North Africa suggests that the model realistically reproduces the total atmospheric column AOD. Finally, we discuss the model results in two sensitivity tests, where we included finer dust particles (less than 1 µm) and changed accordingly the dust bins' mass fraction.

scholarly journals Influence of Random Forest Hyperparameterization on Short-Term Runoff Forecasting in an Andean Mountain Catchment

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 238
Author(s):  
Pablo Contreras ◽  
Johanna Orellana-Alvear ◽  
Paul Muñoz ◽  
Jörg Bendix ◽  
Rolando Célleri
Keyword(s):  
Random Forest ◽  
Model Performance ◽  
Early Warning Systems ◽  
Point Of View ◽  
Lead Times ◽  
Physical Parameters ◽  
Runoff Forecasting ◽  
Spatio Temporal ◽  
Improved Model ◽  
Search Approach

The Random Forest (RF) algorithm, a decision-tree-based technique, has become a promising approach for applications addressing runoff forecasting in remote areas. This machine learning approach can overcome the limitations of scarce spatio-temporal data and physical parameters needed for process-based hydrological models. However, the influence of RF hyperparameters is still uncertain and needs to be explored. Therefore, the aim of this study is to analyze the sensitivity of RF runoff forecasting models of varying lead time to the hyperparameters of the algorithm. For this, models were trained by using (a) default and (b) extensive hyperparameter combinations through a grid-search approach that allow reaching the optimal set. Model performances were assessed based on the R2, %Bias, and RMSE metrics. We found that: (i) The most influencing hyperparameter is the number of trees in the forest, however the combination of the depth of the tree and the number of features hyperparameters produced the highest variability-instability on the models. (ii) Hyperparameter optimization significantly improved model performance for higher lead times (12- and 24-h). For instance, the performance of the 12-h forecasting model under default RF hyperparameters improved to R2 = 0.41 after optimization (gain of 0.17). However, for short lead times (4-h) there was no significant model improvement (0.69 < R2 < 0.70). (iii) There is a range of values for each hyperparameter in which the performance of the model is not significantly affected but remains close to the optimal. Thus, a compromise between hyperparameter interactions (i.e., their values) can produce similar high model performances. Model improvements after optimization can be explained from a hydrological point of view, the generalization ability for lead times larger than the concentration time of the catchment tend to rely more on hyperparameterization than in what they can learn from the input data. This insight can help in the development of operational early warning systems.

scholarly journals Improved tropospheric and stratospheric sulfur cycle in the aerosol–chemistry–climate model SOCOL-AERv2

2019 ◽  
Vol 12 (9) ◽  
pp. 3863-3887 ◽  
Author(s):  
Aryeh Feinberg ◽  
Timofei Sukhodolov ◽  
Bei-Ping Luo ◽  
Eugene Rozanov ◽  
Lenny H. E. Winkel ◽  
...  
Keyword(s):  
Climate Model ◽  
Model Performance ◽  
Stratospheric Aerosol ◽  
Sulfur Cycle ◽  
Sulfate Aerosol ◽  
Tropospheric Chemistry ◽  
Sulfur Deposition ◽  
Aerosol Chemistry ◽  
Deposition Fluxes ◽  
Aerosol Model

Abstract. SOCOL-AERv1 was developed as an aerosol–chemistry–climate model to study the stratospheric sulfur cycle and its influence on climate and the ozone layer. It includes a sectional aerosol model that tracks the sulfate particle size distribution in 40 size bins, between 0.39 nm and 3.2 µm. Sheng et al. (2015) showed that SOCOL-AERv1 successfully matched observable quantities related to stratospheric aerosol. In the meantime, SOCOL-AER has undergone significant improvements and more observational datasets have become available. In producing SOCOL-AERv2 we have implemented several updates to the model: adding interactive deposition schemes, improving the sulfate mass and particle number conservation, and expanding the tropospheric chemistry scheme. We compare the two versions of the model with background stratospheric sulfate aerosol observations, stratospheric aerosol evolution after Pinatubo, and ground-based sulfur deposition networks. SOCOL-AERv2 shows similar levels of agreement as SOCOL-AERv1 with satellite-measured extinctions and in situ optical particle counter (OPC) balloon flights. The volcanically quiescent total stratospheric aerosol burden simulated in SOCOL-AERv2 has increased from 109 Gg of sulfur (S) to 160 Gg S, matching the newly available satellite estimate of 165 Gg S. However, SOCOL-AERv2 simulates too high cross-tropopause transport of tropospheric SO2 and/or sulfate aerosol, leading to an overestimation of lower stratospheric aerosol. Due to the current lack of upper tropospheric SO2 measurements and the neglect of organic aerosol in the model, the lower stratospheric bias of SOCOL-AERv2 was not further improved. Model performance under volcanically perturbed conditions has also undergone some changes, resulting in a slightly shorter volcanic aerosol lifetime after the Pinatubo eruption. With the improved deposition schemes of SOCOL-AERv2, simulated sulfur wet deposition fluxes are within a factor of 2 of measured deposition fluxes at 78 % of the measurement stations globally, an agreement which is on par with previous model intercomparison studies. Because of these improvements, SOCOL-AERv2 will be better suited to studying changes in atmospheric sulfur deposition due to variations in climate and emissions.

scholarly journals Dust Deposition on the Gulf of California Caused by Santa Ana Winds

Atmosphere ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 275 ◽  
Author(s):  
Christian A. Álvarez ◽  
José N. Carbajal ◽  
Luis F. Pineda-Martínez ◽  
José Tuxpan ◽  
David E. Flores
Keyword(s):  
Gulf Of California ◽  
Dust Emission ◽  
Positive Influence ◽  
Dust Particles ◽  
Weather Research And Forecasting ◽  
Western Coast ◽  
Emission Rates ◽  
Dust Deposition ◽  
Santa Ana ◽  
Santa Ana Winds

Numerical simulations revealed a profound interaction between the severe dust storm of 2007 caused by Santa Ana winds and the Gulf of California. The weather research and forecasting model coupled with a chemistry module (WRF-CHEM) and the hybrid single-particle Lagrangian integrated trajectory model (HYSPLIT) allowed for the estimation of the meteorological and dynamic aspects of the event and the dust deposition on the surface waters of the Gulf of California caused by the erosion and entrainment of dust particles from the surrounding desert regions. The dust emission rates from three chosen areas (Altar desert, Sonora coast, and a region between these two zones) and their contribution to dust deposition over the Gulf of California were analyzed. The Altar Desert had the highest dust emission rates and the highest contribution to dust deposition over the Gulf of California, i.e., it has the most critical influence with 96,879 tons of emission and 43,539 tons of dust deposition in the gulf. An increase of chlorophyll-a concentrations is observed coinciding with areas of high dust deposition in the northern and western coast of the gulf. This kind of event could have a significant positive influence over the mineralization and productivity processes in the Gulf of California, despite the soil loss in the eroded regions.

scholarly journals Incremental value of QT interval for the prediction of obstructive coronary artery disease in patients with chest pain

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dong-Hyuk Cho ◽  
Jimi Choi ◽  
Mi-Na Kim ◽  
Hee-Dong Kim ◽  
Soon Jun Hong ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Chest Pain ◽  
Coronary Artery ◽  
Qt Interval ◽  
Obstructive Coronary Artery Disease ◽  
Model Performance ◽  
Clinical Score ◽  
Qtc Prolongation ◽  
Artery Disease ◽  
Improved Model

AbstractIdentification of obstructive coronary artery disease (OCAD) in patients with chest pain is a clinical challenge. The value of corrected QT interval (QTc) for the prediction of OCAD has yet to be established. We consecutively enrolled 1741 patients with suspected angina. The presence of obstructive OCAD was defined as ≥ 50% diameter stenosis by coronary angiography. The pre-test probability was evaluated by combining QTc prolongation with the CAD Consortium clinical score (CAD2) and the updated Diamond-Forrester (UDF) score. OCAD was detected in 661 patients (38.0%). QTc was longer in patients with OCAD compared with those without OCAD (444 ± 34 vs. 429 ± 28 ms, p < 0.001). QTc was increased by the severity of OCAD (P < 0.001). QTc prolongation was associated with OCAD (odds ratio (OR), 2.27; 95% confidence interval (CI), 1.81–2.85). With QTc, the C-statistics increased significantly from 0.68 (95% CI 0.66–0.71) to 0.76 (95% CI 0.74–0.78) in the CAD2 and from 0.64 (95% CI 0.62–0.67) to 0.74 (95% CI 0.72–0.77) in the UDF score, respectively. QT prolongation predicted the presence of OCAD and the QTc improved model performance to predict OCAD compared with CAD2 or UDF scores in patients with suspected angina.

scholarly journals Incremental model breakdown to assess the multi-hypotheses problem

2018 ◽  
Vol 22 (8) ◽  
pp. 4565-4581 ◽  
Author(s):  
Florian U. Jehn ◽  
Lutz Breuer ◽  
Tobias Houska ◽  
Konrad Bestian ◽  
Philipp Kraft
Keyword(s):  
Hydrological Modeling ◽  
Model Performance ◽  
Complex Model ◽  
Model Parameters ◽  
Objective Functions ◽  
Final Model ◽  
Incremental Model ◽  
Model Efficiency ◽  
Improved Model ◽  
Model Structures

Abstract. The ambiguous representation of hydrological processes has led to the formulation of the multiple hypotheses approach in hydrological modeling, which requires new ways of model construction. However, most recent studies focus only on the comparison of predefined model structures or building a model step by step. This study tackles the problem the other way around: we start with one complex model structure, which includes all processes deemed to be important for the catchment. Next, we create 13 additional simplified models, where some of the processes from the starting structure are disabled. The performance of those models is evaluated using three objective functions (logarithmic Nash–Sutcliffe; percentage bias, PBIAS; and the ratio between the root mean square error and the standard deviation of the measured data). Through this incremental breakdown, we identify the most important processes and detect the restraining ones. This procedure allows constructing a more streamlined, subsequent 15th model with improved model performance, less uncertainty and higher model efficiency. We benchmark the original Model 1 and the final Model 15 with HBV Light. The final model is not able to outperform HBV Light, but we find that the incremental model breakdown leads to a structure with good model performance, fewer but more relevant processes and fewer model parameters.

Simulating the action of zeitgebers on a coupled two-oscillator model of the human circadian system

1984 ◽  
Vol 247 (3) ◽  
pp. R418-R426
Author(s):  
P. H. Gander ◽  
R. E. Kronauer ◽  
C. A. Czeisler ◽  
M. C. Moore-Ede
Keyword(s):  
Core Temperature ◽  
Activity Rhythm ◽  
Human Subjects ◽  
Model Performance ◽  
The Other ◽  
Oscillator Model ◽  
Temporal Isolation ◽  
The Core ◽  
Temperature Rhythm ◽  
Rest Activity

Our two-oscillator model was originally designed to describe the circadian rhythms of human subjects maintained in temporal isolation. The performance of this model in response to simulated environmental synchronizing cycles (zeitgebers) is examined here. Six distinct types of synchronization are demonstrated between the x oscillator (postulated to regulate the core temperature rhythm), the y oscillator (postulated to regulate the rest-activity rhythm), and z (the zeitgeber). Four types of synchronization are identifiable, if we consider only the periods of the three oscillators. Both x and y may be synchronized by z; either may synchronize with z while the other exhibits a different period; or x, y, and z may each show different periods. Two further classes of synchronization are discernible when phase criteria are taken into account. When either x or y is on the verge of desynchronizing from the other two oscillators, it undergoes periodic phase modulations while retaining the common overall period. The type of synchronization observed depends on the periods of x, y, and z and on the strength of the z drive. The effects of modifying each of these parameters have been systematically investigated by simulation, and model performance is summarized in terms of range of entrainment "maps." These constitute extensive sets of predictions about expected patterns of entrainment of the core temperature and rest-activity rhythms of human subjects exposed to various environmental zeitgebers. Experimental data are available against which model predictions can be tested.

scholarly journals Emission, transport, and radiative effects of mineral dust from the Taklimakan and Gobi deserts: comparison of measurements and model results

2017 ◽  
Vol 17 (3) ◽  
pp. 2401-2421 ◽  
Author(s):  
Siyu Chen ◽  
Jianping Huang ◽  
Litai Kang ◽  
Hao Wang ◽  
Xiaojun Ma ◽  
...  
Keyword(s):  
East Asia ◽  
Dust Emission ◽  
Dust Concentration ◽  
Dust Particles ◽  
Storm Event ◽  
Gobi Desert ◽  
Radiative Effects ◽  
Dust Aerosols ◽  
Budget Analysis ◽  
Westerly Jets

Abstract. The Weather Research and Forecasting Model with chemistry (WRF-Chem model) was used to investigate a typical dust storm event that occurred from 18 to 23 March 2010 and swept across almost all of China, Japan, and Korea. The spatial and temporal variations in dust aerosols and the meteorological conditions over East Asia were well reproduced by the WRF-Chem model. The simulation results were used to further investigate the details of processes related to dust emission, long-range transport, and radiative effects of dust aerosols over the Taklimakan Desert (TD) and Gobi Desert (GD). The results indicated that weather conditions, topography, and surface types in dust source regions may influence dust emission, uplift height, and transport at the regional scale. The GD was located in the warm zone in advance of the cold front in this case. Rapidly warming surface temperatures and cold air advection at high levels caused strong instability in the atmosphere, which strengthened the downward momentum transported from the middle and low troposphere and caused strong surface winds. Moreover, the GD is located in a relatively flat, high-altitude region influenced by the confluence of the northern and southern westerly jets. Therefore, the GD dust particles were easily lofted to 4 km and were the primary contributor to the dust concentration over East Asia. In the dust budget analysis, the dust emission flux over the TD was 27.2 ± 4.1 µg m−2 s−1, which was similar to that over the GD (29 ± 3.6 µg m−2 s−1). However, the transport contribution of the TD dust (up to 0.8 ton d−1) to the dust sink was much smaller than that of the GD dust (up to 3.7 ton d−1) because of the complex terrain and the prevailing wind in the TD. Notably, a small amount of the TD dust (PM2.5 dust concentration of approximately 8.7 µg m−3) was lofted to above 5 km and transported over greater distances under the influence of the westerly jets. Moreover, the direct radiative forcing induced by dust was estimated to be −3 and −7 W m−2 at the top of the atmosphere, −8 and −10 W m−2 at the surface, and +5 and +3 W m−2 in the atmosphere over the TD and GD, respectively. This study provides confidence for further understanding the climate effects of the GD dust.

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