MetPy: A Meteorological Python Library for Data Analysis and Visualization

May, Ryan M.; Goebbert, Kevin H.; Thielen, Jonathan E.; Leeman, J. R.; Camron, M. Drew; Bruick, Zachary S.; Bruning, Eric C.; Manser, Russell P.; Arms, Sean C.; Marsh, Patrick T.

doi:10.1175/bams-d-21-0125.1

Cited by 77 publications

(67 citation statements)

References 11 publications

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“…The rainfall anomalies were interpreted using Table 1, whereas for the thermodynamic anomalies, values within ±0.99 σ are classified as normal, and values above/below ±0.99 σ are higher/lower than the normal (where σ is the standard deviation). All derived quantities such as the virtual potential temperature, Brunt–Vaisala frequency and equivalent potential temperature (theta‐e) were computed using MetPy version 1.3 (May et al, 2022).…”

Section: Methodsmentioning

confidence: 99%

Environment of severe storm formations over West Africa on the 26‐28 June 2018

Osei

Aryee

Agyekum

et al. 2023

Meteorological Applications

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Understanding the environmental evolution of mesoscale convective systems (MCSs) is critical for forecasting weather in West Africa. This study investigated the thermodynamic and synoptic environments of MCSs over West Africa on 26 (storm 1) and 28 (storm 2) June 2018. Primary datasets used to assess the diurnal evolution of the storms were obtained from ERA5. The results showed a trapped gravity wave, enhanced by a well-established African Easterly Jet and monsoon trough, was responsible for the initiation of storm 1. Both storms also initiated in the presence of several moist lower (925-850 hPa) to mid-tropospheric (600 hPa) cyclonic and anticyclonic vortices, controlling inland moisture advection. The lower troposphere was moistened through moisture advection by the West African westerly jet for storm 1 and the nocturnal low-level jet prior to initiation for storm 2. For both storms, the evolution of outgoing longwave radiation showed a consistent atmosphere of deep afternoon convection. Boundary layer height increased significantly during storm evolution to support the increasing ascent of warm air. Vegetation cover differences may have also likely aided the evolution of storm 2. The passage of gravity waves from decaying storms can aid forecasters to nowcast likely regions of afternoon convection with high accuracy. Under the GCRF African Science for Weather Information and Forecasting Techniques (SWIFT), these findings are crucial in fulfilling the project's aims of improving weather forecasting capability and communication over West Africa.

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Section: Methodsmentioning

confidence: 99%

Environment of severe storm formations over West Africa on the 26‐28 June 2018

Osei

Aryee

Agyekum

et al. 2023

Meteorological Applications

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“…AIRS‐derived variables including q925, Td925, θ e and θ es were computed using MetPy version 1.3 (May et al ., 2022) based on Equations (Holton, 1973) respectively. In the equations, T a is the temperature of air ( K ) at pressure p , p o and p are the reference/initial and final pressures (hPa) respectively, R d is the specific gas constant for dry air ( J /[ kgK ]), c p is the specific heat of dry air at constant pressure ( J /[ kgK ]), L v is the latent heat of vaporization ( kJ /[ kg ]), w s is saturation mixing ratio respectively.

θ_{e} \approx (T_{a} + \frac{L_{v}}{c_{p}} MMR) {((), \frac{p_{o}}{p})}^{\frac{R_{d}}{c_{p}}}

θ_{italices} \approx θ \exp (\frac{L_{v} w_{s}}{c_{p} T_{a}})

…”

Section: Methodsmentioning

confidence: 99%

West Africa's moist convective environment as observed by the Atmospheric InfraRed Sounder (AIRS)

Osei

Ferguson

Quansah

et al. 2023

Intl Journal of Climatology

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Knowledge of the seasonal positioning of the Intertropical Discontinuity (ITD) is critical to understanding seasonal moist convective processes and associated rainfall over West Africa. This study constitutes a new analysis of the seasonality of moist convection over West Africa, relative to the ITD, based on NASA's Atmospheric Infrared Sounder (AIRS) measurements from 2003 to 2018. Results show that AIRS resolves the seasonal march of the ITD, including its inherent diurnal‐scale variations. AIRS captures the north–south daytime skin temperature dipole around the ITD, with greater relative temperatures to the north, especially during March–August. In the vicinity of the nighttime ITD, AIRS profiles indicate increased instability that is characteristic of nocturnal thunderstorm propagation. For seven Ghana weather stations, we show that AIRS positive moisture and equivalent potential temperature anomalies coincide with observed thunderstorm days. On these thunderstorm days, the mean latitude of the AIRS‐derived ITD is displaced 3°, 0.2°, and 2° north of its DJF, MAM, and SON climatological positions, respectively, and 1.2° south in JJA. Among four common thunderstorm initiation indices considered, the K‐index is determined to be most skillful. The findings of this study contribute to the Global Challenges Research Fund, African Science for Weather Information and Forecasting Techniques project's mission to build local tropical weather forecasting capacity and capabilities in West Africa.

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“…These functions include gap-filling and selection functions for interpolation, resampling, clustering, and many more. Being part of a wider ecosystem, users can leverage other Python packages for visualisation (e.g., Matplotlib (Hunter, 2007), MetPy (May et al, 2022)) and optimization and uncertainty analyses (Scipy (Virtanen et al, 2020), SpotPy (Houska et al, 2015)).…”

Section: Software Designmentioning

confidence: 99%

Technical note: Improved handling of potential evapotranspiration in hydrological studies with PyEt

Vremec

Collenteur²,

Birk³

2023

Preprint

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Abstract. Evapotranspiration (ET) is a crucial flux of the hydrological water balance, commonly estimated using (semi-)empirical formulas. The estimated flux may strongly depend on the used formula, adding uncertainty to the outcomes of hydrological models using ET. Climate change may cause additional uncertainty as each formula may respond differently to changes in meteorological input data. To include the effects of model uncertainty and climate change, and facilitate the use of these formulas in a consistent, tested, and reproducible workflow, we present PyEt. PyEt is an open-source Python package for the estimation of daily potential evapotranspiration (PET) using available meteorological data. It allows the application of twenty different PET methods on both time series (Pandas) and gridded datasets (xarray). Most of the implemented methods are benchmarked against literature values and tested with continuous integration to ensure the correctness of the implementation. This article provides an overview of PyEt's capabilities, including the estimation of PET with twenty PET methods for station, and gridded data, a simple procedure for calibrating the empirical coefficients in the alternative PET methods, and estimation of PET under warming and elevated atmospheric CO2 concentration. Further discussion on the advantages of using PyEt estimates as input for hydrological models, sensitivity/uncertainty analyses, and hind/forecasting studies, especially in data-scarce regions, is provided.

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MetPy: A Meteorological Python Library for Data Analysis and Visualization

Cited by 77 publications

References 11 publications

Environment of severe storm formations over West Africa on the 26‐28 June 2018

Environment of severe storm formations over West Africa on the 26‐28 June 2018

West Africa's moist convective environment as observed by the Atmospheric InfraRed Sounder (AIRS)

Technical note: Improved handling of potential evapotranspiration in hydrological studies with PyEt

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