Enhanced short‐range forecasting of sub‐inversion cloudiness in complex terrain

Kann, Alexander; Schellander-Gorgas, Theresa; Wittmann, Christoph

doi:10.1002/asl2.511

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…Many unknowns remain about the details of FLC formation and dissipation. As a result, FLC continues to be difficult to forecast on both long and short time scales [ Kann et al , ]. Daily and diurnal patterns are chaotic, turbulent, and, because of the importance to air traffic, well recorded.…”

Section: Introductionmentioning

confidence: 99%

GOES‐derived fog and low cloud indices for coastal north and central California ecological analyses

Torregrosa

Combs

Peters

2016

Earth and Space Science

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Fog and low cloud cover (FLCC) strongly influences the water, energy, and nutrient flux of coastal ecosystems. Easy-to-use FLCC data are needed to quantify the impacts of FLCC on ecosystem dynamics especially during hot and dry Mediterranean climate summers. Monthly, annual, and decadal FLCC digital maps (indices) were derived for June-September 1999-2009 for coastal California, latitude 34.50°N (south of Monterey Bay) to latitude 41.95°N (north of Crescent City) from 26,000 hourly night and day Geostationary Operational Environmental Satellite (GOES) images. Monthly average FLCC ranges from <2 to 18 hours per day (h/d). Average FLCC over the ocean increases from north (9 h/d) to south (14 h/d), whereas on land, FLCC is highest where land juts into the prevailing NW winds and is lowest in the lee of major capes. FLCC advects farthest inland through low-lying NW ocean-facing valleys. At night, average total hours of FLCC are higher more frequently on land than over the ocean. The interannual FLCC coefficient of variation shows long-term geographic stability that is strongly associated with landform position. FLCC hours per day mapped contours, derived from decadal average FLCC, delineate the commonly used term "fog belt" into FLCC zones with increased locational precision. FLCC indices are available for download from the California Landscape Conservation Cooperative Climate Commons website (http://climate.calcommons.org/datasets/ summertime-fog). FLCC indices can improve analyses of biogeographic and bioclimatic species distribution models; understanding meteorological mechanisms driving FLCC patterns; solar energy feasibility studies; investigations of ecohydrology, evapotranspiration, and agricultural irrigation demand; and viticulture ripening models.

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Section: Introductionmentioning

confidence: 99%

GOES‐derived fog and low cloud indices for coastal north and central California ecological analyses

Torregrosa

Combs

Peters

2016

Earth and Space Science

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“…Several studies have shown that the cycling 3D-Var, 4D-Var and Local Ensemble Transform Kalman Filter (LETKF) improve the precipitation forecast skills [16][17][18][19][20][21][22][23], but despite the development of new parametrization schemes and the increased availability of computational resources over the last years, the prediction of the exact position and timing of convective events is still a challenge in NWP [24][25][26]. In Europe, the most common nowcasting systems, used to detect and forecast hazardous weather in support of Air Traffic Management (ATM) activities, are the Integrated Nowcasting through Comprehensive Analysis (INCA) [27,28] and AROME-NWC [29]. The first system, INCA, covers central Europe with 1 km spatial resolution and uses the NWP forecast provided by the ALADIN or COSMO models, depending on the region.…”

Section: Introductionmentioning

confidence: 99%

Is an NWP-Based Nowcasting System Suitable for Aviation Operations?

et al. 2022

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The growth of air transport demand expected over the next decades, along with the increasing frequency and intensity of extreme weather events, such as heavy rainfalls and severe storms due to climate change, will pose a tough challenge for air traffic management systems, with implications for flight safety, delays and passengers. In this context, the Satellite-borne and IN-situ Observations to Predict The Initiation of Convection for ATM (SINOPTICA) project has a dual aim, first to investigate if very short-range high-resolution weather forecast, including data assimilation, can improve the predictive capability of these events, and then to understand if such forecasts can be suitable for air traffic management purposes. The intense squall line that affected Malpensa, the major airport by passenger traffic in northern Italy, on 11 May 2019 is selected as a benchmark. Several numerical experiments are performed with a Weather Research and Forecasting (WRF) model using two assimilation techniques, 3D-Var in WRF Data Assimilation (WRFDA) system and a nudging scheme for lightning, in order to improve the forecast accuracy and to evaluate the impact of assimilated different datasets. To evaluate the numerical simulations performance, three different verification approaches, object-based, fuzzy and qualitative, are used. The results suggest that the assimilation of lightning data plays a key role in triggering the convective cells, improving both location and timing. Moreover, the numerical weather prediction (NWP)-based nowcasting system is able to produce reliable forecasts at high spatial and temporal resolution. The timing was found to be suitable for helping Air Traffic Management (ATM) operators to compute alternative landing trajectories.

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A Review of High Impact Weather for Aviation Meteorology

Gültepe

Sharman

Williams

et al. 2019

Pure Appl. Geophys.

185

121

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This review paper summarizes current knowledge available for aviation operations related to meteorology and provides suggestions for necessary improvements in the measurement and prediction of weather-related parameters, new physical methods for numerical weather predictions (NWP), and next-generation integrated systems. Severe weather can disrupt aviation operations on the ground or in-flight. The most important parameters related to aviation meteorology are wind and turbulence, fog visibility (Vis) and ceiling, rain and snow amount and rates, icing, ice microphysical parameters, convection and precipitation intensity, microbursts, hail, and lightning. Measurements of these parameters are also functions of sensor response times and measurement thresholds in extreme weather conditions. In addition to these, airport environments can play an important role leading to intensification of extreme weather conditions or high impact weather events, e.g., anthropogenic ice fog. To observe meteorological parameters, new remote sensing platforms, namely wind LIDAR, sodars, radars, and geostationary satellites, and in-situ observations at the surface and in the cloud, as well as aircraft and Unmanned Aerial Vehicles (UAV) mounted sensors, are becoming more common. Because of prediction issues at smaller time and space scales (e.g., <1 km), meteorological forecasts from NWP models need to be continuously improved. Aviation weather forecasts also need to be developed to provide information that represents both deterministic and statistical approaches. In this review, we present available resources and issues for aviation meteorology and evaluate them for required improvements related to measurements, nowcasting, forecasting, and climate change, and emphasize future challenges.

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Enhanced short‐range forecasting of sub‐inversion cloudiness in complex terrain

Cited by 4 publications

References 18 publications

GOES‐derived fog and low cloud indices for coastal north and central California ecological analyses

GOES‐derived fog and low cloud indices for coastal north and central California ecological analyses

Is an NWP-Based Nowcasting System Suitable for Aviation Operations?

A Review of High Impact Weather for Aviation Meteorology

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