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Effect of complex orography on numerical simulations of a downburst event in Spain
Get PDFA downburst is a localized and intense downdraft of air that descends quickly from the middle troposphere and
reaches the Earth’s surface. It is frequently originated by a thunderstorm or a supercell. Downburst winds can
cause significant damage to buildings, infrastructure, and pose a great threat to aviation traffic. On July 1, 2018,
many supercells were spotted near the Zaragoza Airport (Spain), and at least one of them generated a downburst
that affected the airport, causing significant damage in the surrounding area. This event is here simulated using
the Weather Research and Forecasting (WRF-ARW) numerical weather prediction model. Three different WRFARW orography experiments are carried out to investigate if the region’s complex orography has an important
role in supercell and downburst development over the research area. One of the three experiments uses the
default orography as control; another one uses a 90 % smoothed orography, and the third experiment is
configured with a high-resolution dataset. Several atmospheric and convective variables are compared for each
orography experiment. Results show that MUCAPE is clearly higher when the orography complexity is reduced.
The smoothing process leads to a more uniform wind flow, contributing to the formation of numerous supercells.
However, supercells channel through valleys and mountains in the control and high-resolution orography ex
periments, where the surface wind divergences are uniquely reproduced, and the highest reflectivity values are
observed. Moisture advection from the Mediterranean Sea is essential in the process, reaching more deeply into
the study region in the smoothed orography experiment due to the lack of orographic barriers. Orography affects
dynamic and thermodynamic features, which have considerable effects on the formation and development of
downbursts.Carlos Calvo-Sancho acknowledges the grant support from the Spanish Ministerio de Ciencia, Innovación, y Universidades (FPI programmes PRE2020-092343). Moreover, this research has been supported by the Ministerio de Ciencia e Innovación project PID2023-146344OB-I00 (CONSCIENCE) and the ECMWF Special Projects (SPESMART and SPESVALE)
Corpora Newsletter. N. 9 (enero 2025)
No full textBoletín bimestral para la comunicación corporativa de AEMET
Extremos de precipitación y su climatología en Canarias [Póster]
No full textPóster presentado en: XIII Congreso Internacional de la Asociación Española de Climatología "Cambio climático y sociedad", celebrado en San Lorenzo de El Escorial del 22 al 24 Enero de 2025
Star photometry with all-sky cameras to retrieve aerosol optical depth at night-time
Get PDFThis research has been supported by the Ministerio de Ciencia e Innovación (grant nos. TED2021-131211BI00375, PID2021-127588OB-I00, and PID2022-142708NA-I00),
the Consejería de Educación, Junta de Castilla y León (grant no.
CLU-2023-1-05), and the European Cooperation in Science and
Technology (COST Action CA21119 HARMONIA).The lack of aerosol optical depth (AOD) data at night can be partially addressed through moon photometer measurements or fully covered with star photometer observations. However, the limited availability and complexity of star photometers has motivated this study to use all-sky cameras to extract starlight signals and derive AOD at night using star photometry. For this purpose, eight all-sky cameras were configured and deployed in nine different locations to capture raw images with varying exposure times every 2 minutes during the night. This work proposes a novel methodology to extract the starlight signal from the raw data of all-sky cameras and convert it into AOD values. This process consists of the following steps: removing the background image, selecting the pixels and extracting the signal for each star from a predefined list of 56 stars, performing in-situ Langley calibration of the instruments and retrieving the total optical depth (TOD), calculating the effective wavelength for each camera channel, deriving the AOD by subtracting the gas contribution to TOD, and averaging, cloud-screening, and quality-assuring the AOD time series. The AOD time series obtained through this methodology are compared with independent AOD measurements from collocated moon photometers in the nine locations. The obtained results show that the AOD values derived with the proposed method generally correlate with reference values, often achieving correlation coefficients (r) above 0.90. The AOD values retrieved using the cameras tend to overestimate the reference values by approximately 0.02, and exhibit a precision of around 0.03–0.04. The agreement between both datasets varies with wavelength and decreases at high-latitude locations, likely due to the poorer performance of Langley calibration in these regions. AOD values align well with day-to-night transitions obtained by solar photometers, demonstrating their reliability. Despite the slight overestimation, the AOD values derived by this new method approximate the real values and provide coverage throughout the entire night, without requiring the presence of the Moon. Therefore, they serve for studying and monitoring the nocturnal evolution of AOD
Global CH4 fluxes derived from JAXA/GOSAT lower-tropospheric partial column data and the CarbonTracker Europe-CH4 atmospheric inverse model
Get PDFSatellite-driven inversions provide valuable information about methane (CH4) fluxes, but the assimilation of total column-averaged dry-air mole fractions of CH4 (XCH4) has been challenging. This study explores, for the first time, the potential of the new lower tropospheric partial column (pXCH4_LT) GOSAT data, retrieved by the Japan Aerospace Exploration Agency (JAXA), to constrain global and regional CH4 fluxes. Using the CarbonTracker Europe-CH4 atmospheric inverse model, we estimated CH4 fluxes between 2016–2019 by assimilating the JAXA/GOSAT pXCH4_LT and XCH4 data and surface CH4 observations, independently of each other. The Northern Hemisphere CH4 fluxes derived from the JAXA/GOSAT pXCH4_LT data were similar to the estimates derived from the surface observations, but was underestimated by about 35 Tg CH4 year-1 (∼6 % of the global total) using the JAXA/GOSAT XCH4 data. For the Southern Hemisphere, the estimates from the both GOSAT inversions were about 15–30 Tg CH4 year-1 higher than that derived from surface data. The evaluations against independent data from the Atmospheric Tomography Mission aircraft campaign showed good agreement in the lower tropospheric CH4 from the inversions using the JAXA/GOSAT pXCH4_LT and surface data. However, the modelled North-South gradients showed significant overestimation in the upper troposphere and stratosphere, possibly due to relatively uniform inter-hemispheric OH distributions that control CH4 sinks. Overall, we found that the use of the JAXA/GOSAT pXCH4_LT data shows considerable potential in constraining global and regional CH4 fluxes, advancing our understanding of the CH4 budget
