Predicting historical indoor temperatures from available local weather data

2018 ◽  
Vol 12 (4) ◽  
pp. 257-270
Author(s):  
Jeanette J. Varela ◽  
Christine M. Anderson‐Cook ◽  
Brian P. Weaver ◽  
Lawrence O. Ticknor ◽  
Cary B. Skidmore
Keyword(s):  
Weather Data ◽  
Local Weather

Generating hourly local weather data with high spatially resolution and the applications in bioclimatic performance

2019 ◽  
Vol 653 ◽  
pp. 1262-1271 ◽  
Author(s):  
Feng-Yi Lin ◽  
Kuo-Tsang Huang ◽  
Tzu-Ping Lin ◽  
Ruey-Lung Hwang
Keyword(s):  
Weather Data ◽  
Local Weather

scholarly journals Atmospheric Oscillations and Related Synoptic Patterns *

1954 ◽  
Vol 35 (7) ◽  
pp. 301-309 ◽  
Author(s):  
William Donn ◽  
Richard Rommer ◽  
Frank Press ◽  
Maurice Ewing
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Weather Data ◽  
Columbia University ◽  
Air Masses ◽  
Cold Fronts ◽  
Squall Lines ◽  
Short Period ◽  
Local Weather

Records from sensitive microbarovariographs installed at Palisades, N. Y., Columbia University in New York City, U. S. Merchant Marine Academy, Kings Point, L. I. have been studied in connection with synoptic and local weather data. A number of interesting pressure events have been noted in connection with the passage of certain synoptic situations, These include pressure pump lines, squall lines, cold fronts and thunderstorms. Low level turbulence or convection associated with certain air masses at certain times is well-recorded by short-period pressure variations. Conclusions regarding the origin of squall lines are drawn from the empirical evidence given.

Lumped Components Modeling of Double Pass Solar Collector with Porous Matrixes

2013 ◽  
Vol 465-466 ◽  
pp. 216-220
Author(s):  
M.W. Kareem ◽  
Khairul Habib ◽  
S.I. Gilani
Keyword(s):  
Flow Rate ◽  
Solar Collector ◽  
Weather Data ◽  
Double Pass ◽  
Modeling Tools ◽  
Promising Alternative ◽  
Thermal Transfer ◽  
Collector System ◽  
Local Weather ◽  
Good Agreement

In this report, the modeling and simulation of a double pass solar air absorber was carried out using combination of Simscape and Simulink modeling tools. The solar system air mass flow rate and the porous media were critically investigated by using local weather data of Seri Iskandar, Perak, Malaysia. Optimal inlet air flow rate of 0.034kgm-2s-1 was obtained and one of the packed beds, sandstone extended the thermal transfer period of solar collector system by 1150s which displayed good agreement with the reported model and experimental outcomes. The results obtained have shown that it is a promising alternative tool for solar thermal experimentation modeling.

Optimal Surrogate and Neural Network Modeling for Day-Ahead Forecasting of the Hourly Energy Consumption of University Buildings

2017 ◽  
Author(s):  
Payam Ghassemi ◽  
Kaige Zhu ◽  
Souma Chowdhury
Keyword(s):  
Transfer Function ◽  
Surrogate Models ◽  
Weather Data ◽  
Impact Factors ◽  
Neural Network Modeling ◽  
Modeling Framework ◽  
Repair Work ◽  
Building Behavior ◽  
University Buildings ◽  
Local Weather

This paper presents the development and evaluation of Artificial Neural Networks (ANN) based models and optimally selected surrogate models to provide the day-ahead forecast of the hourly-averaged energy load of buildings, by relating it to eight weather parameters as well as the hour of the day. Although ANN and other surrogate models have been used to predict building energy loads in the past, there is a limited understanding of what type of model prescriptions impact their performance as well as how un-recorded impact factors (e.g., human behavior and building repair work) should be accounted for. Here, the recorded energy data of three university buildings, from 9/2013–12/2015, is cleaned and synchronized with the local weather data. The data is then classified into eight classes; weekends and weekdays of Fall/Winter/Spring/Summer semesters. Both Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) NNs are explored. Differing number of hidden layers and transfer function choices are also explored, leading to the choice of the hyperbolic-tangent-sigmoid transfer function and 60 hidden layers. Similarly, an automated surrogate modeling framework is used to select the best models from among a pool of Kriging, RBF, and SVR models. A baseline concept, that uses energy information from the previous day as an added input to the ANN, helps to account for otherwise unrecorded recent changes in the building behavior, leading to improvement in fidelity of up to 30%.

scholarly journals The Importance of Hail Events for Landslides and Bedload Transport in Austrian Alpine Torrents

2021 ◽  
Author(s):  
Mario Schritter ◽  
Thomas Glade
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Control Unit ◽  
Bedload Transport ◽  
Weather Data ◽  
Process Dynamics ◽  
Triggering Conditions ◽  
Thiessen Polygons ◽  
Trigger Mechanisms ◽  
Local Weather

Abstract Landslides and bedload transport can be a threat to people, infrastructure, and vegetation. Many detailed hydrometeorological trigger mechanisms of such natural hazards are still poorly understood. This is in particular valid concerning hail as a trigger of these processes. Therefore, this study aims to determine the influence of hail on landslides and bedload transport in alpine torrents. Based on a generated table from an event register of mountain processes maintained by the Avalanche and Torrent Control Unit (WLV) and weather data provided by the Centre for Meteorology and Geodynamics (ZAMG), 1,573 observed events between 1980 and 2019 in 79 Austrian alpine sites are analysed. Thiessen polygons are used to regionalise local weather data to adjacent regions. The spatial extend of these regions are merged with the registered torrential events. As a result of a stepwise filtering of the used data, the final inventory was created.The results show that 95.1% of the investigated torrential processes triggered by hailstorms are debris flows or debris flow-like transports. Within the study period, a peak of hail-triggered landslides and bedload transport can be recognised in the first 10 days of August in all 39 years. Furthermore, the results suggest that hail is rather a direct than an indirect trigger for landslides and bedload transport.Overall, we conclude that the influence of hail on landslides and bedload transport is significant. Respective hydrometeorological triggering conditions should be included in any regions. Further research for this topic is required to explore the process dynamics in greater detail.

Spacing Analysis of an Inclined Solar Collector Field

2008 ◽  
Author(s):  
S. B. Sadineni ◽  
R. F. Boehm ◽  
R. Hurt
Keyword(s):  
Incident Energy ◽  
Las Vegas ◽  
Computer Code ◽  
Weather Data ◽  
Solar Insolation ◽  
Economic Implications ◽  
Shadow Area ◽  
The Us ◽  
Solar Field ◽  
Local Weather

Spacing between the adjacent collectors in a solar field is an important parameter which effects the shading and hence the energy conversion from collectors. Land value has an important bearing on the spacing between the collectors. A computer code has been developed to predict the change in incident energy on the collectors for various spacing distances between them. The code couples general shading models with the local weather data (TMY2). This can be used to calculate shadow area on the collectors from their adjacent collectors for different times of the day for various spacing distances. Variation of shadow area of the collectors for various spacing distances is presented for various time periods. It has been observed that near sunrise and sunset the percent shading area of a system is generally higher, but its influence on the overall energy collection is relatively less due to the decreased solar insolation available during those times of the day. The variation of annual energy received for various spacing distances is presented. Results are given for locations in the Southwestern region of the US including Las Vegas, Phoenix and Albuquerque. Economic implications of these results are discussed.

scholarly journals Investigation on Wind Power Generation for Different Heights on Bechar, South West of Algeria

2019 ◽  
Vol 01 (02) ◽  
pp. 198-203 ◽  
Author(s):  
Mamer Dahbi ◽  
Mebrouk Sellam ◽  
Ali Benatiallah ◽  
Abdelkader HARROUZ ◽  
◽  
...  
Keyword(s):  
Wind Turbine ◽  
Wind Power ◽  
Renewable Energy Sources ◽  
Energy Resource ◽  
Clean Energy ◽  
Weather Data ◽  
Short Term ◽  
Promising Alternative ◽  
Wind Potential ◽  
Local Weather

The wind energy is one of the most significant and rapidly developing renewable energy sources in the world and it provides a clean energy resource, which is a promising alternative in the short term in Algeria. The main purpose of this paper is to present, the wind potential in Bechar (Southwest of Algeria) and to discuss the potential for electricity generation based on the local weather data for different heights and typical wind turbine characteristics. A case studied investigation allows wind speed and wind power density to be obtained using different hub heights, and the annual power generated and annual operating hours by the wind turbine to be simulated.

scholarly journals Experiencing climate change: revisiting the role of local weather in affecting climate change awareness and related policy preferences

2021 ◽  
Vol 167 (3-4) ◽  
Author(s):  
Lea Gärtner ◽  
Harald Schoen
Keyword(s):  
Climate Change ◽  
Fixed Effects ◽  
Reference Frames ◽  
Weather Conditions ◽  
Policy Preferences ◽  
Weather Data ◽  
Standard Errors ◽  
Theoretical Argument ◽  
Local Weather

AbstractOver the last few years, climate change has risen to the top of the agenda in many Western democracies, backed by a growing share of voters supporting climate protection policies. To understand how and why these changes came about, we revisit the question whether personal experiences with increasingly unusual local weather conditions affect people’s beliefs about climate change and their related attitudes. We first take a closer look at the theoretical underpinnings and extend the theoretical argument to account for the differential impact of different weather phenomena, as well as the role of prior beliefs and individual reference frames. Applying mixed-effects regressions to a novel dataset combining individual-level multi-wave panel survey data from up to 18,010 German voters collected from 2016 to 2019 with weather data from 514 weather stations, we show that personally experiencing unusual or extreme local weather did not shape people’s awareness of climate change as a political problem or their climate policy preferences in a sustained manner. Even among people who may be considered most likely to exhibit such effects, we did not detect them. Moreover, we demonstrate that the common modeling strategy of combining fixed-effects regression with clustered standard errors leads to severely reduced standard errors and substantively different results. We conclude that it cannot be taken for granted that personally experiencing extreme weather phenomena makes a difference in perceptions of climate change and related policy preferences.

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