Special Issue "Climate Variable Forecasting"

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Climatology".

Deadline for manuscript submissions: closed (30 November 2015).

Special Issue Editor

Prof. Dr. John Boland
E-Mail Website
Guest Editor
UniSA STEM, University of South Australia, Mawson Lakes, SA 5095, Australia
Interests: climate change and risk analysis; heat transfer and energy efficient buildings; water harvesting; ecological footprint; sustainable diet
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Special Issue Information

Dear Colleagues,

An efficient use of the fluctuating energy output of photovoltaic (PV) systems, Concentrated Solar Systems (CSP) or wind farms requires reliable forecast information. In fact, this integration into the electricity system can offer a better quality of service if the resource can be predicted with reasonable accuracy. This Special Issue elicits new research on the methods used to forecast climate variables in order to facilitate selection of the appropriate forecast method according to needs. The methods could include statistical, artificial neural network, cloud motion vector, numerical weather prediction, or some combination of these methods.  Note that as well as forecasting wind and solar, consideration of temperature forecasting is also needed. Temperature impacts on the efficiency of PV cells, and also power lines, so knowledge of its future likely values is also of importance. Finally, as well as point forecasts, we need probabilistic forecasts of these variables.

Prof. Dr. John Boland
Guest Editor

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Keywords

  • forecasting
  • renewable resources
  • time series analysis
  • prediction intervals
  • probabilistic forecasting
  • machine learning
  • arima
  • fourier series
  • numerical weather prediction
  • clear sky index
  • spatial-temporal forecasting

Published Papers (9 papers)

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Open AccessArticle
Sub-Seasonal Prediction of the Maritime Continent Rainfall of Wet-Dry Transitional Seasons in the NCEP Climate Forecast Version 2
Atmosphere 2016, 7(2), 28; https://doi.org/10.3390/atmos7020028 - 15 Feb 2016
Cited by 6 | Viewed by 2248
Abstract
This study investigates the characteristics and prediction of the Maritime Continent (MC) rainfall for the transitional periods between wet and dry seasons. Several observational data sets and the output from the 45-day hindcast by the U.S. National Centers for Environmental Prediction (NCEP) Climate [...] Read more.
This study investigates the characteristics and prediction of the Maritime Continent (MC) rainfall for the transitional periods between wet and dry seasons. Several observational data sets and the output from the 45-day hindcast by the U.S. National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2) are used. Results show that the MC experiences a sudden transition from wet season to dry season (WTD) around the 27th pentad, and a gradual transition from dry season to wet season (DTW) around the 59th pentad. Correspondingly, the westerlies over the equatorial Indian Ocean, the easterlies over the equatorial Pacific Ocean, and the Australia High become weaker, contributing to weakening of the convergence over the MC. The subtropical western Pacific high intensifies and extends northeastward during the WTD. The Mascarene High becomes weaker, an anomalous anticyclonic circulation forms over the northeast of the Philippines, and an anomalous low-level convergence occurs over the western MC during the DTW. The NCEP CFSv2 captures the major features of rainfall and related atmospheric circulation when forecast lead time is less than three weeks for WTD and two weeks for DTW. The model predicts a weaker amplitude of the changes in rainfall and related atmospheric circulation for both WTD and DTW as lead time increases. Full article
(This article belongs to the Special Issue Climate Variable Forecasting)
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Open AccessArticle
Influence of ENSO on Regional Indian Summer Monsoon Precipitation—Local Atmospheric Influences or Remote Influence from Pacific
Atmosphere 2016, 7(2), 25; https://doi.org/10.3390/atmos7020025 - 06 Feb 2016
Cited by 16 | Viewed by 3565
Abstract
Using CMIP5 model outputs in different El Niño-Southern Oscillation (ENSO) phases, this work investigates the indicator that could be used as an Index to characterise regional Indian Summer Monsoon (ISM) precipitation. Dividing the Indian subcontinent into five arbitrarily chosen regions, viz. Central North [...] Read more.
Using CMIP5 model outputs in different El Niño-Southern Oscillation (ENSO) phases, this work investigates the indicator that could be used as an Index to characterise regional Indian Summer Monsoon (ISM) precipitation. Dividing the Indian subcontinent into five arbitrarily chosen regions, viz. Central North East (CNE) (18°N–31°N, 86°E–75°E), Hilly (H) (28°N–38°N, 85°E–70°E), North West (NW) (21°N–31°N, 79°E–67°E), North East (NE) (21°N–31°N, 86°E–97°E) and Southern India (S) (18°N–7°N, 73°E–85°E), local wind field and remote influences from the tropical Pacific are considered to improve understanding of regional monsoon rainfall. Results are also compared with observations/reanalysis data to pinpoint areas of shortcomings and agreements. Model results suggest that regional wind velocity, viz. meridional wind component (V) at 850 mb level (V850) and zonal component at 200 mb (U200) and 850 mb (U850) can yield better estimation of local precipitation in regions CNE, H and NW, agreeing well with earlier proposed monsoon Indices. Such observations are independent of different subcategories of ENSO phases and models show good correspondence with observations. Analyses with V at 200 mb (V200) indicate circulation of the upper branch of Hadley cells in regions CNE and S, though suggest the best agreement among models in comparison with other fields, but there are some deviations from observations, indicating a missing mechanism in the models. Using models, this study identified the best parameter in different regions that could be used for the regional monsoon Index, irrespective of various ENSO subcategories; for CNE it is the U200, for H it is U200 and U850, and for NW it is U850. The current analysis, however, fails to indicate anything clearly about the NE region. When focusing on the remote influence from the eastern Pacific region, it is found that atmospheric contribution to regional ISM precipitation fails to indicate consistent roles among models, but sea surface temperature suggests strong connection. However, remote influence from the Central Pacific is captured uniformly in models via zonal components of wind in the H and NW regions. Full article
(This article belongs to the Special Issue Climate Variable Forecasting)
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Open AccessArticle
The Application of TAPM for Site Specific Wind Energy Forecasting
Atmosphere 2016, 7(2), 23; https://doi.org/10.3390/atmos7020023 - 05 Feb 2016
Cited by 4 | Viewed by 2376
Abstract
The energy industry uses weather forecasts for determining future electricity demand variations due to the impact of weather, e.g., temperature and precipitation. However, as a greater component of electricity generation comes from intermittent renewable sources such as wind and solar, weather forecasting techniques [...] Read more.
The energy industry uses weather forecasts for determining future electricity demand variations due to the impact of weather, e.g., temperature and precipitation. However, as a greater component of electricity generation comes from intermittent renewable sources such as wind and solar, weather forecasting techniques need to now also focus on predicting renewable energy supply, which means adapting our prediction models to these site specific resources. This work assesses the performance of The Air Pollution Model (TAPM), and demonstrates that significant improvements can be made to only wind speed forecasts from a mesoscale Numerical Weather Prediction (NWP) model. For this study, a wind farm site situated in North-west Tasmania, Australia was investigated. I present an analysis of the accuracy of hourly NWP and bias corrected wind speed forecasts over 12 months spanning 2005. This extensive time frame allows an in-depth analysis of various wind speed regimes of importance for wind-farm operation, as well as extreme weather risk scenarios. A further correction is made to the basic bias correction to improve the forecast accuracy further, that makes use of real-time wind-turbine data and a smoothing function to correct for timing-related issues. With full correction applied, a reduction in the error in the magnitude of the wind speed by as much as 50% for “hour ahead” forecasts specific to the wind-farm site has been obtained. Full article
(This article belongs to the Special Issue Climate Variable Forecasting)
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Open AccessArticle
Changing Trends and Abrupt Features of Extreme Temperature in Mainland China from 1960 to 2010
Atmosphere 2016, 7(2), 22; https://doi.org/10.3390/atmos7020022 - 02 Feb 2016
Cited by 15 | Viewed by 2257
Abstract
Studies based on the 10th (90th) percentiles as thresholds have been presented to assess moderate extremes in China and globally. However, there has been notably little research on the occurrences of high extremes of warm days and hot days (TX95p and TX99p) and [...] Read more.
Studies based on the 10th (90th) percentiles as thresholds have been presented to assess moderate extremes in China and globally. However, there has been notably little research on the occurrences of high extremes of warm days and hot days (TX95p and TX99p) and cold nights and very cold nights (TN05p and TN01p), based on the 95th and 99th (5th and 1st) percentiles of the daily maximum (minimum) temperature data at a certain station in the period 1971–2000, which have more direct impacts on society and the ecosystem. The trends analyses of cool nights or warm days are based upon the hypothesis that expects a linear trend and no abrupt change. However, abrupt changes in the climate, especially in extreme temperatures, have been pointed to as a major threat to ecosystem services. This study demonstrates that (1) the mean frequencies of TX95p and TX99p increased by 1.80 day/10 year and 0.62 day/10 year, respectively, and that those of TN05p and TN01p decreased by 3.18 day/10 year and 1.01 day/10 year, respectively, in mainland China. Additionally, the TX95p and TX99p increased significantly by 50.42% and 58.21%, respectively, while the TN05p and TN01p of all of the stations decreased significantly by 83.76% and 76.48%, respectively. Finally, (2) the TX95p and TX99p trends underwent abrupt changes in the 1990s or 2000s, but the trends of TN05p and TN01p experienced abrupt changes in the late 1970s and early 1980s. After the abrupt change points, the trend of warm and hot days increased more rapidly than before in most regions, but the trend of cold days and very cold days decreased more slowly than before in most regions, which indicates a greater risk of heat waves in the future. Full article
(This article belongs to the Special Issue Climate Variable Forecasting)
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Open AccessArticle
Solar Forecasting in a Challenging Insular Context
Atmosphere 2016, 7(2), 18; https://doi.org/10.3390/atmos7020018 - 29 Jan 2016
Cited by 11 | Viewed by 2062
Abstract
This paper aims at assessing the accuracy of different solar forecasting methods in the case of an insular context. Two sites of La Réunion Island, Le Tampon and Saint-Pierre, are chosen to do the benchmarking exercise. Réunion Island is a tropical island with [...] Read more.
This paper aims at assessing the accuracy of different solar forecasting methods in the case of an insular context. Two sites of La Réunion Island, Le Tampon and Saint-Pierre, are chosen to do the benchmarking exercise. Réunion Island is a tropical island with a complex orography where cloud processes are mainly governed by local dynamics. As a consequence, Réunion Island exhibits numerous micro-climates. The two aforementioned sites are quite representative of the challenging character of solar forecasting in the case of a tropical island with complex orography. Hence, although distant from only 10 km, these two sites exhibit very different sky conditions. This work focuses on day-ahead and intra-day solar forecasting. Day-ahead solar forecasts are provided by the European Center for Medium-Range Weather Forecast (ECMWF). This organization maintains and runs the Numerical Weather Prediction (NWP) model named Integrated Forecast System (IFS). In this work, post-processing techniques are applied to refine the output of the IFS model for day-ahead forecasting. Statistical models like a recursive linear model or a nonlinear model such as an artificial neural network are used to produce the intra-day solar forecasts. It is shown that a combination of the IFS model and the neural network model further improves the accuracy of the forecasts. Full article
(This article belongs to the Special Issue Climate Variable Forecasting)
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Open AccessArticle
Review and Extension of Suitability Assessment Indicators of Weather Model Output for Analyzing Decentralized Energy Systems
Atmosphere 2015, 6(12), 1871-1888; https://doi.org/10.3390/atmos6121835 - 03 Dec 2015
Cited by 4 | Viewed by 3267
Abstract
Electricity from renewable energy sources (RES-E) is gaining more and more influence in traditional energy and electricity markets in Europe and around the world. When modeling RES-E feed-in on a high temporal and spatial resolution, energy systems analysts frequently use data generated by [...] Read more.
Electricity from renewable energy sources (RES-E) is gaining more and more influence in traditional energy and electricity markets in Europe and around the world. When modeling RES-E feed-in on a high temporal and spatial resolution, energy systems analysts frequently use data generated by numerical weather models as input since there is no spatial inclusive and comprehensive measurement data available. However, the suitability of such model data depends on the research questions at hand and should be inspected individually. This paper focuses on new methodologies to carry out a performance evaluation of solar irradiation data provided by a numerical weather model when investigating photovoltaic feed-in and effects on the electricity grid. Suitable approaches of time series analysis are researched from literature and applied to both model and measurement data. The findings and limits of these approaches are illustrated and a new set of validation indicators is presented. These novel indicators complement the assessment by measuring relevant key figures in energy systems analysis: e.g., gradients in energy supply, maximum values and volatility. Thus, the results of this paper contribute to the scientific community of energy systems analysts and researchers who aim at modeling RES-E feed-in on a high temporal and spatial resolution using weather model data. Full article
(This article belongs to the Special Issue Climate Variable Forecasting)
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Open AccessArticle
A Method for Deriving the Boundary Layer Mixing Height from MODIS Atmospheric Profile Data
Atmosphere 2015, 6(9), 1346-1361; https://doi.org/10.3390/atmos6091346 - 15 Sep 2015
Cited by 15 | Viewed by 3229
Abstract
The planetary boundary layer is the medium of energy, moisture, momentum and pollutant exchange between the surface and the atmosphere. In this paper, a method to derive the boundary layer mixing height (MH) was introduced and applied over the Heihe river basin. Atmospheric [...] Read more.
The planetary boundary layer is the medium of energy, moisture, momentum and pollutant exchange between the surface and the atmosphere. In this paper, a method to derive the boundary layer mixing height (MH) was introduced and applied over the Heihe river basin. Atmospheric profiles from the MODerate Resolution Imaging Sepctroradiometer (MODIS) instrument onboard the NASA-Aqua satellite were used for the high spatial resolution of this method. A gap-filling method was used to replace missing MODIS data. In situ MH data were also calculated from HIWATER (Heihe Watershed Allied Telemetry Experimental Research) and WATER (Watershed Allied Telemetry Experimental Research) observational radiosonde sounding data from 2008 and 2012 using the Richardson number method combined with a subjective method. The MH occurs where there is an abrupt decrease in the MR (water vapor mixing ratio). The minimum vertical gradient of the MR is used to determine the MH. The method has an average RMSE of 370 m under clear skies and convective conditions. The seasonal variation in the MH at the Gaoya radiosonde station is also presented. The study demonstrates that remote sensing methodologies can successfully estimate the MH without the help of field measurements. Full article
(This article belongs to the Special Issue Climate Variable Forecasting)
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Open AccessArticle
Topography and Data Mining Based Methods for Improving Satellite Precipitation in Mountainous Areas of China
Atmosphere 2015, 6(8), 983-1005; https://doi.org/10.3390/atmos6080983 - 24 Jul 2015
Cited by 12 | Viewed by 2764
Abstract
Topography is a significant factor influencing the spatial distribution of precipitation. This study developed a new methodology to evaluate and calibrate the Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA) products by merging geographic and topographic information. In the proposed method, firstly, the [...] Read more.
Topography is a significant factor influencing the spatial distribution of precipitation. This study developed a new methodology to evaluate and calibrate the Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA) products by merging geographic and topographic information. In the proposed method, firstly, the consistency rule was introduced to evaluate the fitness of satellite rainfall with measurements on the grids with and without ground gauges. Secondly, in order to improve the consistency rate of satellite rainfall, genetic programming was introduced to mine the relationship between the gauge rainfall and location, elevation and TMPA rainfall. The proof experiment and analysis for the mean annual satellite precipitation from 2001–2012, 3B43 (V7) of TMPA rainfall product, was carried out in eight mountainous areas of China. The result shows that the proposed method is significant and efficient both for the assessment and improvement of satellite precipitation. It is found that the satellite rainfall consistency rates in the gauged and ungauged grids are different in the study area. In addition, the mined correlation of location-elevation-TMPA rainfall can noticeably improve the satellite precipitation, both in the context of the new criterion of the consistency rate and the existing criteria such as Bias and RMSD. The proposed method is also efficient for correcting the monthly and mean monthly rainfall of 3B43 and 3B42RT. Full article
(This article belongs to the Special Issue Climate Variable Forecasting)
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Open AccessErratum
Erratum: Feng et al. A Method for Deriving the Boundary Layer Mixing Height from MODIS Atmospheric Profile Data. Atmosphere, 2015, 6, 1346-1361
Atmosphere 2016, 7(3), 37; https://doi.org/10.3390/atmos7030037 - 10 Mar 2016
Cited by 1 | Viewed by 1509
Abstract
The authors would like to correct the acknowledgements of this article [1] as follows:[...] Full article
(This article belongs to the Special Issue Climate Variable Forecasting)
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