Forecasting Summertime Surface Temperature and Precipitation in the Mexico City Metropolitan Area: Sensitivity of the WRF Model to Land Cover Changes

Lopez-Bravo, Clemente; Caetano, Ernesto; Magaña, Víctor

doi:10.3389/feart.2018.00006

Cited by 10 publications

(12 citation statements)

References 34 publications

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“…For the Valley of Mexico, various efforts have been made to improve and evaluate the quality of the numerical weather prediction (NWP) based on the WRF model [28,[30][31][32][33]. These evaluations have considered fundamental aspects, such as the quality of land cover data, initial and boundary conditions, spin-up time, horizontal resolution, and different land surface model (LSM) schemes.…”

Section: Wrf Model Configurationmentioning

confidence: 99%

“…Later, the lake system experienced several modifications and nowadays it is almost completely desiccated, remaining only around 1.3% of its original area (Figure 1a). The climate in the Valley of Mexico is influenced by tropical and mid-latitude meteorological systems, and it has suffered significant changes [3,6,9,10,18,[25][26][27][28] due to the ancient lake system desiccation [3,6,18]. At the present time, its climate is characterized by two well-defined seasons: the dry season, which spans from November to May, and the rainy season, which runs from June to October.…”

Section: Introductionmentioning

confidence: 99%

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Impacts of the Desiccated Lake System on Precipitation in the Basin of Mexico City

et al. 2019

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Mexico City constitutes one of the largest concentrations of population on the planet and is settled in a valley that, before the 16th century, had a lake system. The lakes were desiccated artificially, and currently, only small lakes remain. The impact of the lake system desiccation on precipitation was studied by performing numerical experiments: with the ancient lake system and without it. The experiments were carried out with the Weather Research and Forecasting (WRF) model coupled with a lake model for two months, using identical initial and boundary conditions, where only the system and lake physics were changed. The mean daily accumulated precipitation reduced when the system was removed. Additionally, the hourly distribution of rainfall changed from a relatively small diurnal variability when there was a lake system to a larger variability with a peak in the afternoon when the system was removed. Extreme precipitation events became more intense in the simulations with lakes. When the lakes were removed, the diurnal temperature range increased, and the boundary layer height became more variable, with a higher daily maximum. The results presented here show that the WRF-Lake model leads to opposite results compared to those with a non-coupled lake.

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Section: Wrf Model Configurationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Impacts of the Desiccated Lake System on Precipitation in the Basin of Mexico City

et al. 2019

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“…In the past, research on environmental impacts due to LULCC for Mexico City has been conducted with both observational data and Numerical Weather Prediction (NWP) models [25][26][27][28][29][30][31]. Jáuregui [26] studied the changes in temperature, humidity, rainfall, and fog due to LULCC using observational data from northeast Mexico City.…”

Section: Introductionmentioning

confidence: 99%

“…They also found that the timing of intense precipitation changed from 1900 to 1600 local time (UTC-6h) due to decreased urbanization (close to pre-LULCC). Studies such as those of López-Espinoza et al [29] and López-Bravo et al [31] have analyzed the sensitivity of the WRF model only to changes in the urban cover data and documented an improvement in the weather forecasts. However, these studies were focused on the proper representation of the urban land cover, and limited attention was given to the effect of an accurate representation of other LULC information, such as forest land, agricultural land, rangeland, barren land, etc.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Impact of Land Use and Land Cover Data Representation on Weather Forecast Quality: A Case Study in Central Mexico

et al. 2020

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In atmospheric modeling, an accurate representation of land cover is required because such information impacts water and energy budgets and, consequently, the performance of models in simulating regional climate. This study analyzes the impact of the land cover data on an operational weather forecasting system using the Weather Research and Forecasting (WRF) model for central Mexico, with the aim of improving the quality of the operative forecast. Two experiments were conducted using different land cover datasets: a United States Geological Survey (USGS) map and an updated North American Land Change Monitoring System (NALCMS) map. The experiments were conducted as a daily 120 h forecast for each day of January, April, July, and September of 2012, and the near-surface temperature, wind speed, and hourly precipitation were analyzed. Both experiments were compared with observations from meteorological stations. The statistical analysis of this study showed that wind speed and near-surface temperature prediction may be further improved with the updated and more accurate NALCMS dataset, particularly in the forecast covering 48 to 72 h. The Root Mean Square Error (RMSE) of the average wind speed reached a maximum reduction of up to 1.2 m s−1, whereas for the near-surface temperature there was a reduction of up to 0.6 °C. The RMSE of the average hourly precipitation was very similar between both experiments, however the location of precipitation was modified.

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“…Geographical datasets affect land‐atmosphere interface conditions by altering heat flux, hydrological cycle, and topographic relief, which are key factors influencing meteorological variables prescribed in models (Avissar & Schmidt, 1998; Chen & Dudhia, 2001; Ezber et al, 2007; LeMone et al, 2008; Pielke et al, 2011). Hence, adequately describing land surface features can ensure the precision of meteorological simulation by a weather forecasting model when combined with proper physical parametrization schemes (Lopez‐Bravo et al, 2018). The Weather Research and Forecasting (WRF) model contains various static geographical datasets concerning land cover, topography, soil texture, and vegetation.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Impacts of Land Cover and Soil Texture Changes on Simulated Surface Wind and Temperature

Liu

et al. 2020

Earth and Space Science

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In this study, Chinese Academy of Sciences land cover dataset (CAS_LC) and soil texture dataset (CAS_ST) as well as Tsinghua University land cover dataset (TU_LC) were incorporated into the Weather Research and Forecasting (WRF) model to evaluate the impacts of land cover and soil texture changes on the surface wind and air temperature as compared with outdated default datasets. Six modeling scenarios including single updating for the three new datasets, combined updating of new datasets (CAS_LC + CAS_ST, TU_LC + CAS_ST), and default datasets are designed. WRF simulations were conducted with three resolutions (9, 3, and 1 km) for the period of 14 July to 31 September 2017 over Harbin. Results of the 10-m wind speed, 10-m wind direction, and 2-m air temperature (T2) were evaluated against WRF default datasets (WLS). Results show that TU_LC-related simulations with lower mean absolute error (MAE) demonstrated the usefulness of this dataset in the wind speed simulation, while the changing soil texture exerted a limited effect on modeled wind. CAS_LC improved simulated wind direction and T2. Significant changes in the three variables were frequently induced by urban and built-up land or water bodies related transformations. The 3-km grid resolution was sufficient to reasonably simulate the surface winds and air temperature. The roughness length was a main factor disturbing the wind speed, while the land cover transformation was responsible for the changes in surface temperature and heat fluxes, thereby affecting T2 simulation.

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Forecasting Summertime Surface Temperature and Precipitation in the Mexico City Metropolitan Area: Sensitivity of the WRF Model to Land Cover Changes

Cited by 10 publications

References 34 publications

Impacts of the Desiccated Lake System on Precipitation in the Basin of Mexico City

Impacts of the Desiccated Lake System on Precipitation in the Basin of Mexico City

Assessing the Impact of Land Use and Land Cover Data Representation on Weather Forecast Quality: A Case Study in Central Mexico

Evaluating the Impacts of Land Cover and Soil Texture Changes on Simulated Surface Wind and Temperature

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