scholarly journals Modeling the Diurnal Variability of Agricultural Ammonia in Bakersfield, California during CalNex

2016 ◽  
Author(s):  
C. R. Lonsdale ◽  
J. D. Hegarty ◽  
K. Cady-Pereira ◽  
M. J. Alvarado ◽  
D. K. Henze ◽  
...  
Keyword(s):  
Air Quality ◽  
Diurnal Cycle ◽  
Vertical Mixing ◽  
Model Performance ◽  
Model Bias ◽  
Night Time ◽  
Diurnal Variability ◽  
Aircraft Observations ◽  
Diurnal Profile ◽  
Surface Observations

Abstract. NH3 retrievals from the NASA Tropospheric Emission Spectrometer (TES), as well as surface and aircraft observations of NH3(g) and submicron NH4(p), are to used to evaluate modelled concentrations of NH3(g) and NH4(p) from the Community Multiscale Air Quality (CMAQ) model in the San Joaquin Valley (SJV) during the California Research at the Nexus of Air Quality and Climate Change (CalNex) campaign. We find that simulations of NH3 driven with the California Air Resources Board (CARB) CalNex emission inventory are qualitatively and spatially consistent with TES satellite observations, with a correlation coefficient (r2) of 0.54. However, the surface observations at Bakersfield indicate a missing diurnal cycle in the model bias, with CMAQ overestimating surface NH3 at night and underestimating it during the day. The surface, satellite, and aircraft observations all suggest that the afternoon NH3 emissions in the CARB inventory are underestimated by at least a factor of two, while the night-time overestimate of NH3(g) is likely due to a combination of overestimated NH3 emissions, underestimated deposition, and insufficient vertical mixing in the WRF meteorological fields used to drive CMAQ. We used the surface observations at Bakersfield to derive an empirical diurnal cycle of NH3 emissions in the SJV, in which night-time and midday emissions differed by about a factor of 4.5. Adding this diurnal profile to the CMAQ simulations while keeping the daily NH3 emissions constant at the CARB values significantly improved the model performance at night, but sizable errors (up to 15 ppbv) in night-time NH3 remain, likely due to remaining errors in vertical mixing at night. The model performance is slightly degraded during the afternoon when the diurnal cycle is adjusted, but this may reflect relatively small (~ 20 %) errors in the total NH3 emissions rather than remaining errors in the diurnal cycle. Running CMAQv5.0.2 with bi-directional NH3 flux also improves model performance on a similar scale, while combining bi-directional NH3 fluxes and adjusted emissions significantly reduces the model bias at night.

scholarly journals Modeling the diurnal variability of agricultural ammonia in Bakersfield, California, during the CalNex campaign

2017 ◽  
Vol 17 (4) ◽  
pp. 2721-2739 ◽  
Author(s):  
Chantelle R. Lonsdale ◽  
Jennifer D. Hegarty ◽  
Karen E. Cady-Pereira ◽  
Matthew J. Alvarado ◽  
Daven K. Henze ◽  
...  
Keyword(s):  
Air Quality ◽  
Diurnal Cycle ◽  
Management Practices ◽  
Fertilizer Application ◽  
Satellite Observations ◽  
Model Errors ◽  
Model Bias ◽  
Diurnal Variability ◽  
Aircraft Observations ◽  
Surface Observations

Abstract. NH3 retrievals from the NASA Tropospheric Emission Spectrometer (TES), as well as surface and aircraft observations of NH3(g) and submicron NH4(p), are used to evaluate modeled concentrations of NH3(g) and NH4(p) from the Community Multiscale Air Quality (CMAQ) model in the San Joaquin Valley (SJV) during the California Research at the Nexus of Air Quality and Climate Change (CalNex) campaign. We find that simulations of NH3 driven with the California Air Resources Board (CARB) emission inventory are qualitatively and spatially consistent with TES satellite observations, with a correlation coefficient (r2) of 0.64. However, the surface observations at Bakersfield indicate a diurnal cycle in the model bias, with CMAQ overestimating surface NH3 at night and underestimating it during the day. The surface, satellite, and aircraft observations all suggest that daytime NH3 emissions in the CARB inventory are underestimated by at least a factor of 2, while the nighttime overestimate of NH3(g) is likely due to a combination of overestimated NH3 emissions and underestimated deposition.Running CMAQ v5.0.2 with the bi-directional NH3 scheme reduces NH3 concentrations at night and increases them during the day. This reduces the model bias when compared to the surface and satellite observations, but the increased concentrations aloft significantly increase the bias relative to the aircraft observations. We attempt to further reduce model bias by using the surface observations at Bakersfield to derive an empirical diurnal cycle of NH3 emissions in the SJV, in which nighttime and midday emissions differ by about a factor of 4.5. Running CMAQv5.0.2 with a bi-directional NH3 scheme together with this emissions diurnal profile further reduces model bias relative to the surface observations. Comparison of these simulations with the vertical profile retrieved by TES shows little bias except for the lowest retrieved level, but the model bias relative to flight data aloft increases slightly. Our results indicate that both diurnally varying emissions and a bi-directional NH3 scheme should be applied when modeling NH3(g) and NH4(p) in this region. The remaining model errors suggest that the bi-directional NH3 scheme in CMAQ v5.0.2 needs further improvements to shift the peak NH3 land–atmosphere flux to earlier in the day. We recommend that future work include updates to the current CARB NH3 inventory to account for NH3 from fertilizer application, livestock, and other farming practices separately; adding revised information on crop management practices specific to the SJV region to the bi-directional NH3 scheme; and top-down studies focused on determining the diurnally varying biases in the canopy compensation point that determines the net land–atmosphere NH3 fluxes.

scholarly journals The diurnal cycle of entrainment and detrainment in LES of the Southern Ocean driven by observed surface fluxes and waves

2021 ◽  
Author(s):  
William G. Large ◽  
Edward G. Patton ◽  
Peter P. Sullivan
Keyword(s):  
Boundary Layer ◽  
Southern Ocean ◽  
Diurnal Cycle ◽  
Time History ◽  
Surface Flux ◽  
Surface Fluxes ◽  
Buoyancy Flux ◽  
Stokes Drift ◽  
Night Time ◽  
Diurnal Variability

AbstractEmpirical rules for both entrainment and detrainment are developed from LES of the Southern Ocean boundary layer when the turbulence, stratification and shear cannot be assumed to be in equilibrium with diurnal variability in surface flux and wave (Stokes drift) forcing. A major consequence is the failure of down-gradient eddy viscosity, which becomes more serious with Stokes drift and is overcome by relating the angle between the stress and shear vectors to the orientations of Lagrangian shear to the surface and of local Eulerian shear over five meters. Thus, the momentum flux can be parameterized as a stress magnitude and this empirical direction. In addition, the response of a deep boundary layer to sufficiently strong diurnal heating includes boundary layer collapse and the subsequent growth of a morning boundary layer, whose depth is empirically related to the time history of the forcing, as are both morning detrainment and afternoon entrainment into weak diurnal stratification. Below the boundary layer, detrainment rules give the maximum buoyancy flux and its depth, as well a specific stress direction. Another rule relates both afternoon and night-time entrainment depth and buoyancy flux to surface layer turbulent kinetic energy production integrals. These empirical relationships are combined with rules for boundary layer transport to formulate two parameterizations; one based on eddy diffusivity and viscosity profiles and another on flux profiles of buoyancy and of stress magnitude. Evaluations against LES fluxes show the flux profiles to be more representative of the diurnal cycle, especially with Stokes drift.

scholarly journals Understanding sources of organic aerosol during CalNex-2010 using the CMAQ-VBS

2016 ◽  
Vol 16 (6) ◽  
pp. 4081-4100 ◽  
Author(s):  
Matthew C. Woody ◽  
Kirk R. Baker ◽  
Patrick L. Hayes ◽  
Jose L. Jimenez ◽  
Bonyoung Koo ◽  
...  
Keyword(s):  
Air Quality ◽  
Vehicle Emissions ◽  
Model Performance ◽  
Organic Aerosol ◽  
Photochemical Oxidation ◽  
Basis Set ◽  
Monitoring Networks ◽  
Routine Monitoring ◽  
Diurnal Profile ◽  
Formation Efficiency

Abstract. Community Multiscale Air Quality (CMAQ) model simulations utilizing the traditional organic aerosol (OA) treatment (CMAQ-AE6) and a volatility basis set (VBS) treatment for OA (CMAQ-VBS) were evaluated against measurements collected at routine monitoring networks (Chemical Speciation Network (CSN) and Interagency Monitoring of Protected Visual Environments (IMPROVE)) and those collected during the 2010 California at the Nexus of Air Quality and Climate Change (CalNex) field campaign to examine important sources of OA in southern California. Traditionally, CMAQ treats primary organic aerosol (POA) as nonvolatile and uses a two-product framework to represent secondary organic aerosol (SOA) formation. CMAQ-VBS instead treats POA as semivolatile and lumps OA using volatility bins spaced an order of magnitude apart. The CMAQ-VBS approach underpredicted organic carbon (OC) at IMPROVE and CSN sites to a greater degree than CMAQ-AE6 due to the semivolatile POA treatment. However, comparisons to aerosol mass spectrometer (AMS) measurements collected at Pasadena, CA, indicated that CMAQ-VBS better represented the diurnal profile and primary/secondary split of OA. CMAQ-VBS SOA underpredicted the average measured AMS oxygenated organic aerosol (OOA, a surrogate for SOA) concentration by a factor of 5.2, representing a considerable improvement to CMAQ-AE6 SOA predictions (factor of 24 lower than AMS). We use two new methods, one based on species ratios (SOA/ΔCO and SOA/Ox) and another on a simplified SOA parameterization, to apportion the SOA underprediction for CMAQ-VBS to slow photochemical oxidation (estimated as 1.5 ×  lower than observed at Pasadena using −log(NOx : NOy)), low intrinsic SOA formation efficiency (low by 1.6 to 2 ×  for Pasadena), and low emissions or excessive dispersion for the Pasadena site (estimated to be 1.6 to 2.3 ×  too low/excessive). The first and third factors are common to CMAQ-AE6, while the intrinsic SOA formation efficiency for that model is estimated to be too low by about 7 × . From source-apportioned model results, we found most of the CMAQ-VBS modeled POA at the Pasadena CalNex site was attributable to meat cooking emissions (48 %, consistent with a substantial fraction of cooking OA in the observations). This is compared to 18 % from gasoline vehicle emissions, 13 % from biomass burning (in the form of residential wood combustion), and 8 % from diesel vehicle emissions. All "other" inventoried emission sources (e.g., industrial, point, and area sources) comprised the final 13 %. The CMAQ-VBS semivolatile POA treatment underpredicted AMS hydrocarbon-like OA (HOA) + cooking-influenced OA (CIOA) at Pasadena by a factor of 1.8 compared to a factor of 1.4 overprediction of POA in CMAQ-AE6, but it did capture the AMS diurnal profile of HOA and CIOA well, with the exception of the midday peak. Overall, the CMAQ-VBS with its semivolatile treatment of POA, SOA from intermediate volatility organic compounds (IVOCs), and aging of SOA improves SOA model performance (though SOA formation efficiency is still 1.6–2 ×  too low). However, continued efforts are needed to better understand assumptions in the parameterization (e.g., SOA aging) and provide additional certainty to how best to apply existing emission inventories in a framework that treats POA as semivolatile, which currently degrades existing model performance at routine monitoring networks. The VBS and other approaches (e.g., AE6) require additional work to appropriately incorporate IVOC emissions and subsequent SOA formation.

scholarly journals Spatial, temporal and vertical distribution of ammonia concentrations over Europe – comparing a static and dynamic approach with WRF-Chem

2015 ◽  
Vol 15 (16) ◽  
pp. 22935-22973 ◽  
Author(s):  
M. Werner ◽  
M. Kryza ◽  
C. Geels ◽  
T. Ellermann ◽  
C. Ambelas Skjøth
Keyword(s):  
Diurnal Cycle ◽  
Model Performance ◽  
Ammonia Concentration ◽  
Ammonia Emission ◽  
Weather Research And Forecasting ◽  
Dynamic Approach ◽  
Boundary Layer Height ◽  
Diurnal Profile ◽  
Static Approach ◽  
Agricultural Areas

Abstract. The study focuses on the application of a dynamic ammonia emission into the Weather Research and Forecasting Chemistry model (WRF-Chem) and the influence on the simulated ammonia concentrations and the overall model performance. We have focused on agricultural ammonia sources and have analysed both hourly and daily patterns of ammonia emissions and concentrations at measurement sites located in agricultural areas or influenced by this activity. For selected episodes, we have also investigated the 3-D patterns of the ammonia concentrations in the atmosphere. The application of the dynamic ammonia emission into the WRF-Chem model (the "DYNAMIC" simulation) results in an improvement of the modelled daily ammonia concentrations in comparison to a static approach (the "BASE" simulation), which is currently widely used in chemical transport models. In the case of hourly resolution, we have observed an improvement for the DYNAMIC approach for the winter and autumn seasons, but for the entire year the modelled hourly ammonia peaks are shifted toward the afternoon hours if compared with measurements. This study indicates that the current description of the diurnal cycle of the ammonia concentration from fields is not accurate and more research is needed in order to improve the processes that describe the emission from fertilised fields. The results suggest that the governing processes in relation to the diurnal cycle are the atmospheric mixing and the emission strength. Therefore, an improved description of the diurnal profile of ammonia concentrations within atmospheric models requires a better description of the planetary boundary layer height and a stronger daily pattern of ammonia emission, e.g. through increased evaporation or increased fluxes from the surface.

scholarly journals Systematic bias in evaluating chemical transport models with maximum daily 8-hour average (MDA8) surface ozone for air quality applications

2019 ◽  
Author(s):  
Katherine R. Travis ◽  
Daniel J. Jacob
Keyword(s):  
Air Quality ◽  
Diurnal Cycle ◽  
Surface Ozone ◽  
Chemical Transport ◽  
Systematic Bias ◽  
Transport Models ◽  
Chemical Transport Models ◽  
Aircraft Observations ◽  
Southeast Us ◽  
Quality Policy

Abstract. Chemical transport models typically evaluate their simulation of surface ozone with observations of the maximum daily 8-hour average (MDA8) concentration, which is the standard air quality policy metric. This requires successful simulation of the surface ozone diurnal cycle including nighttime depletion, but models are generally biased high at night because of difficulty in resolving the stratified conditions near the surface. We quantify the problem with the GEOS-Chem model for the Southeast US during the NASA SEAC4RS aircraft campaign in August–September 2013. The model is unbiased relative to the daytime mixed layer aircraft observations but has a +5 ppb bias relative to MDA8 surface ozone observations. The model also does not capture observed occurrences of

A Combined Local and Nonlocal Closure Model for the Atmospheric Boundary Layer. Part II: Application and Evaluation in a Mesoscale Meteorological Model

2007 ◽  
Vol 46 (9) ◽  
pp. 1396-1409 ◽  
Author(s):  
Jonathan E. Pleim
Keyword(s):  
Boundary Layer ◽  
Air Quality ◽  
Atmospheric Boundary Layer ◽  
Mesoscale Model ◽  
Evaluation Studies ◽  
Vertical Mixing ◽  
Model Performance ◽  
State University ◽  
Meteorological Model ◽  
Wind Profilers

Abstract A new combined local and nonlocal closure atmospheric boundary layer model called the Asymmetric Convective Model, version 2, (ACM2) was described and tested in one-dimensional form and was compared with large-eddy simulations and field data in Part I. Herein, the incorporation of the ACM2 into the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) is described. Model simulations using the MM5 with the ACM2 are made for the summer of 2004 and evaluated through comparison with surface meteorological measurements, rawinsonde profile measurements, and observed planetary boundary layer (PBL) heights derived from radar wind profilers. Overall model performance is as good as or better than similar MM5 evaluation studies. The MM5 simulations with the ACM2 compare particularly well to PBL heights derived from radar wind profilers during the afternoon hours. The ACM2 is designed to simulate the vertical mixing of any modeled quantity realistically for both meteorological models and air quality models. The next step, to be described in a subsequent article, is to incorporate the ACM2 into the Community Multiscale Air Quality (CMAQ) model for testing and evaluation.

scholarly journals Filling the gaps of in situ hourly PM<sub>2.5</sub> concentration data with the aid of empirical orthogonal function analysis constrained by diurnal cycles

2020 ◽  
Vol 13 (3) ◽  
pp. 1213-1226 ◽  
Author(s):  
Kaixu Bai ◽  
Ke Li ◽  
Jianping Guo ◽  
Yuanjian Yang ◽  
Ni-Bin Chang
Keyword(s):  
Air Quality ◽  
Empirical Orthogonal Function ◽  
Diurnal Cycle ◽  
Ambient Air ◽  
Concentration Data ◽  
Diurnal Variability ◽  
Orthogonal Function ◽  
Good Prediction Accuracy ◽  
Data Gaps ◽  
Pm2.5 Concentration

Abstract. Data gaps in surface air quality measurements significantly impair the data quality and the exploration of these valuable data sources. In this study, a novel yet practical method called diurnal-cycle-constrained empirical orthogonal function (DCCEOF) was developed to fill in data gaps present in data records with evident temporal variability. The hourly PM2.5 concentration data retrieved from the national ambient air quality monitoring network in China were used as a demonstration. The DCCEOF method aims to reconstruct the diurnal cycle of PM2.5 concentration from its discrete neighborhood field in space and time firstly and then predict the missing values by calibrating the reconstructed diurnal cycle to the level of valid PM2.5 concentrations observed at adjacent times. The statistical results indicate a high frequency of data gaps in our retrieved hourly PM2.5 concentration record, with PM2.5 concentration measured on about 40 % of the days suffering from data gaps. Further sensitivity analysis results reveal that data gaps in the hourly PM2.5 concentration record may introduce significant bias to its daily averages, especially during clean episodes at which PM2.5 daily averages are observed to be subject to larger uncertainties compared to the polluted days (even in the presence of the same amount of missingness). The cross-validation results indicate that our suggested DCCEOF method has a good prediction accuracy, particularly in predicting daily peaks and/or minima that cannot be restored by conventional interpolation approaches, thus confirming the effectiveness of the consideration of the local diurnal variation pattern in gap filling. By applying the DCCEOF method to the hourly PM2.5 concentration record measured in China from 2014 to 2019, the data completeness ratio was substantially improved while the frequency of days with gapped PM2.5 records reduced from 42.6 % to 5.7 %. In general, our DCCEOF method provides a practical yet effective approach to handle data gaps in time series of geophysical parameters with significant diurnal variability, and this method is also transferable to other data sets with similar barriers because of its self-consistent capability.

scholarly journals Mechanisms controlling primary and new production in a global ecosystem model – Part II: the role of the upper ocean short-term periodic and episodic mixing events

2006 ◽  
Vol 3 (4) ◽  
pp. 1115-1148
Author(s):  
E. E. Popova ◽  
A. C. Coward ◽  
G. A. Nurser ◽  
B. de Cuevas ◽  
T. R. Anderson
Keyword(s):  
Primary Production ◽  
Diurnal Cycle ◽  
Model Performance ◽  
Ecosystem Model ◽  
Ecosystem Dynamics ◽  
Biogeochemical Model ◽  
Atmospheric Variability ◽  
New Production ◽  
Diurnal Variability ◽  
Episodic Mixing

Abstract. The use of 6 h, daily, weekly and monthly atmospheric forcing resulted in dramatically different predictions of plankton productivity in a global 3-D coupled physical-biogeochemical model. Resolving the diurnal cycle of atmospheric variability by use of 6 h forcing, and hence also diurnal variability in UML depth, produced the largest difference, reducing predicted global primary and new production by 25% and 10% respectively relative to that predicted with daily and weekly forcing. This decrease varied regionally, being a 30% reduction in equatorial areas and 25% at moderate and high latitudes. A 10% increase in the primary production was seen in the peripheries of the oligotrophic gyres. By resolving the diurnal cycle, model performance was significantly improved with respect to several common problems: underestimated primary production in the oligotrophic gyres; overestimated primary production in the Southern Ocean; overestimated magnitude of the spring bloom in the subarctic Pacific Ocean, and overestimated primary production in equatorial areas. The result of using 6 h forcing on predicted ecosystem dynamics was profound, the effects persisting far beyond the hourly timescale, and having major consequences for predicted global and new production on an annual basis.

scholarly journals Urban Air Quality Modeling Using Low-Cost Sensor Network and Data Assimilation in the Aburrá Valley, Colombia

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 91
Author(s):  
Santiago Lopez-Restrepo ◽  
Andres Yarce ◽  
Nicolás Pinel ◽  
O.L. Quintero ◽  
Arjo Segers ◽  
...  
Keyword(s):  
Air Quality ◽  
Data Assimilation ◽  
Transport Model ◽  
Cost Model ◽  
Low Cost ◽  
Model Performance ◽  
Monitoring Network ◽  
Correlation Factor ◽  
Chemical Transport Model ◽  
High Quality

The use of low air quality networks has been increasing in recent years to study urban pollution dynamics. Here we show the evaluation of the operational Aburrá Valley’s low-cost network against the official monitoring network. The results show that the PM2.5 low-cost measurements are very close to those observed by the official network. Additionally, the low-cost allows a higher spatial representation of the concentrations across the valley. We integrate low-cost observations with the chemical transport model Long Term Ozone Simulation-European Operational Smog (LOTOS-EUROS) using data assimilation. Two different configurations of the low-cost network were assimilated: using the whole low-cost network (255 sensors), and a high-quality selection using just the sensors with a correlation factor greater than 0.8 with respect to the official network (115 sensors). The official stations were also assimilated to compare the more dense low-cost network’s impact on the model performance. Both simulations assimilating the low-cost model outperform the model without assimilation and assimilating the official network. The capability to issue warnings for pollution events is also improved by assimilating the low-cost network with respect to the other simulations. Finally, the simulation using the high-quality configuration has lower error values than using the complete low-cost network, showing that it is essential to consider the quality and location and not just the total number of sensors. Our results suggest that with the current advance in low-cost sensors, it is possible to improve model performance with low-cost network data assimilation.

scholarly journals The diurnal cycle of cloud profiles over land and ocean between 51° S and 51° N, seen by the CATS spaceborne lidar from the International Space Station

2018 ◽  
Vol 18 (13) ◽  
pp. 9457-9473 ◽  
Author(s):  
Vincent Noel ◽  
Hélène Chepfer ◽  
Marjolaine Chiriaco ◽  
John Yorks
Keyword(s):  
High Altitude ◽  
International Space Station ◽  
Diurnal Cycle ◽  
Space Station ◽  
Cloud Fraction ◽  
Vertical Profiles ◽  
Diurnal Variability ◽  
International Space ◽  
Low Level ◽  
Diurnal Cycles

Abstract. We document, for the first time, how detailed vertical profiles of cloud fraction (CF) change diurnally between 51∘ S and 51∘ N, by taking advantage of 15 months of measurements from the Cloud-Aerosol Transport System (CATS) lidar on the non-sun-synchronous International Space Station (ISS). Over the tropical ocean in summer, we find few high clouds during daytime. At night they become frequent over a large altitude range (11–16 km between 22:00 and 04:00 LT). Over the summer tropical continents, but not over ocean, CATS observations reveal mid-level clouds (4–8 km above sea level or a.s.l.) persisting all day long, with a weak diurnal cycle (minimum at noon). Over the Southern Ocean, diurnal cycles appear for the omnipresent low-level clouds (minimum between noon and 15:00) and high-altitude clouds (minimum between 08:00 and 14:00). Both cycles are time shifted, with high-altitude clouds following the changes in low-altitude clouds by several hours. Over all continents at all latitudes during summer, the low-level clouds develop upwards and reach a maximum occurrence at about 2.5 km a.s.l. in the early afternoon (around 14:00). Our work also shows that (1) the diurnal cycles of vertical profiles derived from CATS are consistent with those from ground-based active sensors on a local scale, (2) the cloud profiles derived from CATS measurements at local times of 01:30 and 13:30 are consistent with those observed from CALIPSO at similar times, and (3) the diurnal cycles of low and high cloud amounts (CAs) derived from CATS are in general in phase with those derived from geostationary imagery but less pronounced. Finally, the diurnal variability of cloud profiles revealed by CATS strongly suggests that CALIPSO measurements at 01:30 and 13:30 document the daily extremes of the cloud fraction profiles over ocean and are more representative of daily averages over land, except at altitudes above 10 km where they capture part of the diurnal variability. These findings are applicable to other instruments with local overpass times similar to CALIPSO's, such as all the other A-Train instruments and the future EarthCARE mission.

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