Mean radiant temperature from global-scale numerical weather prediction models

In human biometeorology, the estimation of mean radiant temperature (MRT) is generally considered challenging. This work presents a general framework to compute the MRT at the global scale for a human subject placed in an outdoor environment and irradiated by solar and thermal radiation both directly and diffusely. The proposed framework requires as input radiation fluxes computed by numerical weather prediction (NWP) models and generates as output gridded globe-wide maps of MRT. It also considers changes in the Sun’s position affecting radiation components when these are stored by NWP models as an accumulated-over-time quantity. The applicability of the framework was demonstrated using NWP reanalysis radiation data from the European Centre for Medium-Range Weather Forecasts. Mapped distributions of MRT were correspondingly computed at the global scale. Comparison against measurements from radiation monitoring stations showed a good agreement with NWP-based MRT (coefficient of determination greater than 0.88; average bias equal to 0.42 °C) suggesting its potential as a proxy for observations in application studies

Intra-hour cloud index forecasting with data assimilation

We introduce a computational framework to forecast cloud index (CI)fields for up to one hour on a spatial domain that covers a city. Such intra-hour CI forecasts are important to produce solar power forecasts of utility scale solar power and distributed rooftop solar. Our method combines a 2D advection model with cloud motion vectors (CMVs)derived from a mesoscale numerical weather prediction (NWP)model and sparse optical flow acting on successive, geostationary satellite images. We use ensemble data assimilation to combine these sources of cloud motion information based on the uncertainty of each data source. Our technique produces forecasts that have similar or lower root mean square error than reference techniques that use only optical flow, NWP CMV fields, or persistence. We describe how the method operates on three representative case studies and present results from 39 cloudy days

Estimating 1min rain rate distributions from numerical weather prediction

Internationally recognized prognostic models of rain fade on terrestrial and Earth-space EHF links rely fundamentally on distributions of one-minute rain rates. Currently, in Rec. ITU-R P.837-6, these distributions are generated using the Salonen Poiares-Baptista method where one-minute rain rate distributions are estimated from long-term average annual accumulations provided by Numerical Weather Products (NWP). This paper investigates an alternative to this method based on the distribution of six-hour accumulations available from the same NWPs. Rain rate fields covering the UK, produced by the Nimrod network of radars, are integrated to estimate the accumulations provided by NWP and these are linked to distributions of fine scale rain rates. The proposed method makes better use of the available data. It is verified on 15 NWP regions spanning the UK and the extension to other regions is discussed

Transitional Jobs for Ex-Prisoners: Early Impacts from a Random Assignment Evaluation of the Center for Employment Opportunities (CEO) Prisoner Reentry Program

After one year, CEO's transitional jobs program generated a large but short-lived increase in employment for ex-prisoners. A subgroup of recently released prisoners showed positive effects on recidivism: They were less likely to have their parole revoked, to be convicted of a felony, and to be reincarcerated than the control group

The Impact of Digital Tools on Student Writing and How Writing is Taught in Schools

In a survey of Advanced Placement and National Writing Project teachers, a majority say digital tools encourage students to be more invested in their writing by encouraging personal expression and providing a wider audience for their work. Most also say digital tools make teaching writing easier, despite an increasingly ambiguous line between formal and informal writing and students' poor understanding of issues such as plagiarism and fair use