DOI: 10.5281/zenodo.15169329
title: Observational dataset used in "Urban multi-season sensible heat fluxes from multiple large aperture scintillometry paths: variability and operational numerical weather prediction skill"

description: These data are used in Chapter 3, “Urban multi-season sensible heat fluxes from multiple large aperture scintillometry paths: variability and operational numerical weather prediction skill” in the University of Reading thesis "Urban surface-atmosphere exchanges: scintillometry observations and NWP evaluation" submitted by Beth Saunders, 2024. The observation dataset consists of 109 days across 2016-2018. Some of the experimental setup is also described in Saunders et. al 2024: “Methodology to evaluate numerical weather predictions using large aperture scintillometry sensible heat fluxes: demonstration in London”, DOI: https://doi.org/10.1002/qj.4837. File names and subdirectories are named in the format year + day of year (DOY).

AWS processed:

Processed and quality-control checked data from a Davis Vantage Pro Plus located in the city of London (Saunders et al. 2024).

CNR4 processed:

Processed and quality-control checked data from a Kipp & Zonen CNR4 radiometer either in the city of London (‘KSSW’, Saunders et al. 2024) or on BT Tower (‘BTT’).

LAS raw:

Raw data from four scintillometer paths in London; ‘BCT-IMU’, ‘IMU-BTT’, ‘BTT-BCT’ and ‘SCT-SWT’. The experimental setup of ‘BCT-IMU’ is described by Saunders et al. 2024. Three of the four paths (‘BCT-IMU’, ‘BTT-BCT’, ‘SCT-SWT’) consist of a single beam Kipp and Zonen MKII LAS (850 nm wavelength) sensor. ‘IMU-BTT’ is a Scintec BLS900 sensor.

LAS source areas:

Source areas for four scintillometer paths. Data are derived using the methodology as described by Saunders et al. 2024 (see Fig. 2), and were written using the ‘scintools’ python code (10.5281/zenodo.7434074). Digital surface models used for these cases are also included as part of the ‘scintools’ zenodo repository.

Source areas for the specific case study days used are processed using the python code ‘scint_fp’ (included in 10.5281/zenodo.7434153) using automatic weather station data included here (in the directory AWS processed). csv files included in each subdirectory of ‘LAS_Source_Areas’ are the inputs given to ‘scint_fp’.

Source areas are calculated every hour using inputs averaged over the last 10 minutes of that our (time-ending). For example, a 1200 source area is calculated using meteorological conditions averaged over 1150-1200. The end of each file name indicates the time period (time ending) of which the source area applies.

LAS processed:

Processed data for four scintillometer paths. Data were derived using the methodology as described by Saunders et al. 2024 (see Fig. 3), and written using the ‘scint_flux’ python code (10.5281/zenodo.7434143) and using scintillometer source areas derived from the ‘scintools’ python code (10.5281/zenodo.7434074).

Files ending with PERIOD_VAR_## refer to the averaging period performed on the LAS raw data as number in minutes (where ## is 1, 10, and 60 minutes). Files with a name including ‘sa10min_ending’ use source areas calculated every hour with input meteorological conditions averaged over 10 minutes.
description: The authors acknowledge the funding and support from the NERC Case studentship (NE/N008103/1) and ERC urbisphere (855005).