Identification

Title

Impact of assimilating uncrewed aircraft system observations on river valley fog prediction

Abstract

The impact of assimilating targeted uncrewed aircraft system (UAS) observations on the prediction of radiation and river valley fog is assessed using observing system experiments (OSEs). Two multirotor UASs were deployed during Frequent in situ Observations above Ground for Modeling and Advanced Prediction of fog (FOGMAP) which took place during the summer of 2022 in northern Kentucky. Targeted UAS missions were flown to sample the spatiotemporal variability of temperature and moisture in the vicinity of the Cincinnati/Northern Kentucky International Airport. During each mission, the UAS performed near-continuous profiling at two locations between the surface to 120 m AGL throughout the night. Data denial experiments were performed using the ensemble adjustment Kalman filter available in NSF NCAR’s Data Assimilation Research Testbed (DART) to determine the impact of assimilating UAS observations on the skill of analyses and forecasts issued during potential fog events. Simulations that only assimilated conventional observations tended to have a dry bias in the analyses and forecasts. The dry bias in the analyses was reduced in experiments that assimilated UAS observations leading to improved probabilistic predictions of fog. Sensitivity tests revealed that the ensemble mean analyses were improved when assimilating UAS observations of specific humidity rather than relative humidity (RH) due to the existence of a cold bias near the surface and the negative covariance between RH and temperature. It was also found that either the assumed observation error variance of (1 g kg −1 ) 2 or the ensemble spread of the background specific humidity was too large since their sum tended to overestimate the root-mean-square error (RMSE) of the predicted ensemble mean values.

Resource type

document

Resource locator

Unique resource identifier

code

https://n2t.net/ark:/85065/d7n01bvr

codeSpace

Dataset language

eng

Spatial reference system

code identifying the spatial reference system

Classification of spatial data and services

Topic category

geoscientificInformation

Keywords

Keyword set

keyword value

Text

originating controlled vocabulary

title

Resource Type

reference date

date type

publication

effective date

2016-01-01T00:00:00Z

Geographic location

West bounding longitude

East bounding longitude

North bounding latitude

South bounding latitude

Temporal reference

Temporal extent

Begin position

End position

Dataset reference date

date type

publication

effective date

2024-11-01T00:00:00Z

Frequency of update

Quality and validity

Lineage

Conformity

Data format

name of format

version of format

Constraints related to access and use

Constraint set

Use constraints

Limitations on public access

None

Responsible organisations

Responsible party

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata on metadata

Metadata point of contact