Variability of the Mixed-Layer Height Over Mexico City

García‐Franco, Jorge L.; Stremme, Wolfgang; Bezanilla, Alejandro; Ruiz‐Angulo, Angel; Grutter, Michel

doi:10.1007/s10546-018-0334-x

Cited by 34 publications

(40 citation statements)

References 15 publications

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“…Details are given in Appendix B. For the calculation of the Rayleigh cross section Q Ray , we follow the implementation of Goody and Yung (1989) (their Eq. 7.37); see also Platt et al (2007) (their Eq.…”

Section: Input For Gasesmentioning

confidence: 99%

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NO<sub>2</sub> vertical profiles and column densities from MAX-DOAS measurements in Mexico City

et al. 2019

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Abstract. We present a new numerical code, Mexican MAX-DOAS Fit (MMF), developed to retrieve profiles of different trace gases from the network of MAX-DOAS instruments operated in Mexico City. MMF uses differential slant column densities (dSCDs) retrieved with the QDOAS (Danckaert et al., 2013) software. The retrieval is comprised of two steps, an aerosol retrieval and a trace gas retrieval that uses the retrieved aerosol profile in the forward model for the trace gas. For forward model simulations, VLIDORT is used (e.g., Spurr et al., 2001; Spurr, 2006, 2013). Both steps use constrained least-square fitting, but the aerosol retrieval uses Tikhonov regularization and the trace gas retrieval optimal estimation. Aerosol optical depth and scattering properties from the AERONET database, averaged ceilometer data, WRF-Chem model data, and temperature and pressure sounding data are used for different steps in the retrieval chain. The MMF code was applied to retrieve NO2 profiles with 2 degrees of freedom (DOF = 2) from spectra of the MAX-DOAS instrument located at the Universidad Nacional Autónoma de México (UNAM) campus. We describe the full error analysis of the retrievals and include a sensitivity exercise to quantify the contribution of the uncertainties in the aerosol extinction profiles to the total error. A data set comprised of measurements from January 2015 to July 2016 was processed and the results compared to independent surface measurements. We concentrate on the analysis of four single days and additionally present diurnal and annual variabilities from averaging the 1.5 years of data. The total error, depending on the exact counting, is 14 %–20 % and this work provides new and relevant information about NO2 in the boundary layer of Mexico City.

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Section: Input For Gasesmentioning

confidence: 99%

“…For the Rayleigh scattering cross section, we implement Eq. (7.37) from Goody and Yung (1989) and Eq. (19.5) from Platt et al (2007); see Eq.…”

Section: (B7)mentioning

confidence: 99%

NO<sub>2</sub> vertical profiles and column densities from MAX-DOAS measurements in Mexico City

et al. 2019

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“…This inversion was located only about 1,500–2,000 m above ground level, and given that maximum 2‐m air temperatures only reached between 25 and 28 °C (not shown), the inversion acted to limit the growth of the ABL to no more than about 2,000 m above ground level. This ABL depth is about 1,000 m smaller than the March climatology reported by García‐Franco et al (). The thermal inversion also prevented the development of deep convective clouds and precipitation, allowing strong UV‐B radiation to continue through the afternoon hours.…”

Section: Resultsmentioning

confidence: 99%

A Multiscale Analysis of the Tropospheric and Stratospheric Mechanisms Leading to the March 2016 Extreme Surface Ozone Event in Mexico City

et al. 2019

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This study analyzed the physical mechanisms behind a multiday high surface ozone (O3) event in Mexico City in March 2016. In early March, a strong zonal jet stream over the Pacific Ocean amplified and underwent wave breaking. An unusual cutoff low pressure system then migrated across central Mexico, with 200‐hPa geopotential heights among the lowest in the reanalysis historical record (1948 to present). A tropopause fold on the west side of the cutoff low transported O3‐rich air from the stratosphere into the troposphere and resulted in high O3 concentrations all the way to the surface. The stratospheric intrusion began on 09 March and ended on 12 March, but surface O3 concentrations continued to rise, peaking on 14 March. Given the deep boundary layer observed on 12 March, it is very likely that remnants of the stratospheric O3 in the midtroposphere at the regional level could have been entrained into the boundary layer. Furthermore, our analysis indicates that as the cutoff low progressed eastward, the pronounced low‐level thermal inversion and reduced ventilation observed on subsequent days (13–15 March) contributed to elevated concentrations of O3 precursors, which together with strong UV radiation, led to efficient photochemical production of O3 and to the very large values observed in several of the monitoring stations (up to 210 parts per billion on 14 March). Finally, mitigation measures put into place by authorities reduced both the number of vehicles on the road and the resulting nighttime titration, possibly extending the duration of dangerous O3 levels in the city.

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“…For the analysis presented in this study the ML height is estimated based on the maximum negative gradient in the NRB profile along with a modified wavelet transform (Brooks, 2003;García-Franco et al, 2018) technique for minimizing the noise. In the algorithm, firstly the height of largest negative gradient is estimated and assessed for the possibility of a floor or false detection based on rapid change in ML height between two adjacent time-steps.…”

Section: Discussionmentioning

confidence: 99%

“…A variety of techniques for ML height detection has been suggested, which includes the application of a gradient technique on the range corrected signal (RCS) (Flamant et al, 1997;García-Franco et al, 2018) and the logarithm of the RCS (He et al, 2006), maximum of the RCS temporal variance (Hooper and Eloranta, 1986), wavelet analysis of the RCS profile (Cohn and Angevine, 2000), extended Kalman filter method (Lange et al, 2014), and the cubic root gradient of the RCS profile (Yang et al, 2017). Although fully automated, ML height detection is restricted by the limitations of various techniques Ware et al, 2016) in clearly identifying different features in the lower troposphere.…”

Section: Introductionmentioning

confidence: 99%

Mixing Layer Height Retrievals From MiniMPL Measurements in the Chiang Mai Valley: Implications for Particulate Matter Pollution

et al. 2019

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Variability of the Mixed-Layer Height Over Mexico City

Cited by 34 publications

References 15 publications

NO<sub>2</sub> vertical profiles and column densities from MAX-DOAS measurements in Mexico City

NO<sub>2</sub> vertical profiles and column densities from MAX-DOAS measurements in Mexico City

A Multiscale Analysis of the Tropospheric and Stratospheric Mechanisms Leading to the March 2016 Extreme Surface Ozone Event in Mexico City

Mixing Layer Height Retrievals From MiniMPL Measurements in the Chiang Mai Valley: Implications for Particulate Matter Pollution

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Variability of the Mixed-Layer Height Over Mexico City

Cited by 34 publications

References 15 publications

NO&lt;sub&gt;2&lt;/sub&gt; vertical profiles and column densities from MAX-DOAS measurements in Mexico City

NO&lt;sub&gt;2&lt;/sub&gt; vertical profiles and column densities from MAX-DOAS measurements in Mexico City

A Multiscale Analysis of the Tropospheric and Stratospheric Mechanisms Leading to the March 2016 Extreme Surface Ozone Event in Mexico City

Mixing Layer Height Retrievals From MiniMPL Measurements in the Chiang Mai Valley: Implications for Particulate Matter Pollution

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NO<sub>2</sub> vertical profiles and column densities from MAX-DOAS measurements in Mexico City

NO<sub>2</sub> vertical profiles and column densities from MAX-DOAS measurements in Mexico City