CSTools R package bringing state-of-the-arts postprocessing methods to seasonal-to-decadal forecast users

2020 ◽  
Author(s):  
Nuria Perez-Zanon ◽  
Louis-Philippe Caron ◽  
M. Carmen Alvarez-Castro ◽  
Lauriane Batté ◽  
Susanna Corti ◽  
...  
Keyword(s):  
Development Strategy ◽  
R Package ◽  
Forecast Combination ◽  
Climate Data ◽  
Seasonal Forecasts ◽  
Public And Private ◽  
Forecast Performance ◽  
Operational Systems ◽  
Common Framework ◽  
Multiple Variables

<p>The availability of climate data has never been larger, as evidenced by the development of the Copernicus Climate Change Service. However, availability of climate data does not automatically translate into usability and sophisticated post-processing is often required to turn these climate data into user-relevant climate information allowing them to develop and implement strategies of adaptation to climate variability and to trigger decisions. </p><p>Developed under the umbrella of the ERA4CS Medscope project by multiple European partners, here we present an R package currently in development, which aims to provide tools to exploit dynamical seasonal forecasts such as to provide information relevant to public and private stakeholders at the seasonal timescale. This toolbox, called CSTools (short for Climate Service Tools), contains process-based methods for forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination and multivariate verification, as well as basic and advanced tools to obtain tailored products. </p><p>In addition to presenting some of the tools that are contained in the package, we also present a short overview of the development strategy adopted for this toolbox. The latter relies on a version controlling system established such as to allow scientists and developers to work within a common framework using a platform where they can exchange with other developers, test the various functionalities and discuss issues arising from the work, amongst other things. Furthermore, we will also present some vignettes, which are one of the mechanisms that allows users to understand and visualize the capabilities of CSTools. For instance, CSTools contains a step by step vignette showing how to use and visualize the output of MultivarRMSE, which gives an indication of the forecast performance (RMSE) for multiple variables simultaneously. </p><p>While the extensive community of R users offers the opportunity of merging climate forecaster experts with final users, CSTools can also be used by other communities, such as Python users through the interface rpy. Finally, the publication of this package on CRAN (the Comprehensive R Archive Network) makes it easily accessible to interested users and ensures its proper functioning on different operational systems. </p>

scholarly journals The CSTools (v4.0) Toolbox: from Climate Forecasts to Climate Forecast Information

2021 ◽  
Author(s):  
Núria Pérez-Zanón ◽  
Louis-Philippe Caron ◽  
Silvia Terzago ◽  
Bert Van Schaeybroeck ◽  
Llorenç Lledó ◽  
...  
Keyword(s):  
R Package ◽  
Climate Forecast ◽  
Forecast Combination ◽  
Post Processing ◽  
Seasonal Forecasts ◽  
Climate Forecasts ◽  
Extreme Wind ◽  
Forecast Data ◽  
Extreme Wind Speed

Abstract. Despite the wealth of existing climate forecast data, only a small part is effectively exploited for sectoral applications. A major cause of this is the lack of integrated tools that allow the translation of data into useful and skilful climate information. This barrier is addressed through the development of an R package. CSTools is an easy-to-use toolbox designed and built to assess and improve the quality of climate forecasts for seasonal to multi–annual scales. The package contains process-based state-of-the-art methods for forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination and multivariate verification, as well as basic and advanced tools to obtain tailored products. Due to the design of the toolbox in individual functions, the users can develop their own post-processing chain of functions as shown in the use cases presented in this manuscript: the analysis of an extreme wind speed event, the generation of seasonal forecasts of snow depth based on the SNOWPACK model and the post-processing of data to be used as input for the SCHEME hydrological model.

scholarly journals POLITICAL REGIONAL TOURISM IN CIVIL SOCIETY PERSPECTIVE (Profile of Development Strategy of Situ Bagendit Tourism Object, Banyuresmi District, Garut Regency, West Java Province)

2019 ◽  
Vol 1 (1) ◽  
pp. 24-50
Author(s):  
Hasan Mustapa
Keyword(s):  
Civil Society ◽  
Development Strategy ◽  
The State ◽  
Main Question ◽  
Public And Private ◽  
Regional Tourism ◽  
Role Of The State ◽  
Development Politics ◽  
Tourism Potential ◽  
Society Perspective

The main question of this study is how the politics of tourism development in the Situ Bagendit area is in the perspective of civil society. The theoretical foundation used in this paper is the concept of Civil Society expressed by Janoski (1998: 12) which states that the idea of civil society rests on intensive discourse between the four domains, namely the state, markets, public and private / private. To clarify the understanding of the main statements, it was elaborated through several conceptions about the politics of development and regional tourism with various variations. So that the good relations that are correlational in nature and the relevance between the politics of development are positive and the progress of regional tourism through an effective review of civil society implementation The role of the state is very effective by delegating ownership from the center to the district for the management of Situ Bagendit. In contrast, in the realm of the market there seems to be less contribution. There has not been a productive effort in the public domain for the development of this tourist attraction. Similarly, personal awareness to develop this tourism potential so that going international is still low. Every tourism potential can become a regional icon that is able to compete on an international scale. One of the strategies is with productive development politics in the synergy between the state and related institutions.

Characterising recent drought events using current reanalysis and remote-sensing soil moisture products within a common framework

2021 ◽  
Author(s):  
Martin Hirschi ◽  
Bas Crezee ◽  
Sonia I. Seneviratne
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Land Surface ◽  
Root Zone ◽  
Microwave Remote Sensing ◽  
Agricultural Drought ◽  
Climate Data ◽  
Data Store ◽  
Common Framework ◽  
Long Term Trends

<p>Drought events cause multiple impacts on the environment, the society and the economy. Here, we analyse recent major drought events with different metrics using a common framework. The analysis is based on current reanalysis (ERA5, ERA5-Land, MERRA-2) and merged remote-sensing products (ESA-CCI soil moisture, gridded satellite soil moisture from the Copernicus Climate Data Store), focusing on soil moisture (or agricultural) drought. The events are characterised by their severity, magnitude, duration and spatial extent, which are calculated from standardised daily anomalies of surface and root-zone soil moisture. We investigate the ability of the different products to represent the droughts and set the different events in context to each other. The considered products also offer opportunities for drought monitoring since they are available in near-real time.</p><p>All investigated products are able to represent the investigated drought events. Overall, ERA5 and ERA5-Land often show the strongest, and the remote-sensing products often weaker responses based on surface soil moisture. The weaker severities of the events in the remote-sensing products are both related to shorter event durations as well as less pronounced average negative standardised soil moisture anomalies, while the magnitudes (i.e., the minimum of the standardised anomalies over time) are comparable to the reanalysis products. Differing global distributions of long-term trends may explain some differences in the drought responses of the products. Also, the lower penetration depth of microwave remote sensing compared to the top layer of the involved land surface models could explain the partly weaker negative standardized soil moisture anomalies in the remote-sensing products during the investigated events. In the root zone (based on the reanalysis products), the drought events often show prolonged durations, but weaker magnitudes and smaller spatial extents.</p>

Tourism forecast combination using the stochastic frontier analysis technique

2019 ◽  
Vol 26 (7) ◽  
pp. 1086-1107 ◽  
Author(s):  
Ji Wu ◽  
Xian Cheng ◽  
Stephen Shaoyi Liao
Keyword(s):  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Multiple Criteria Decision Making ◽  
Forecast Combination ◽  
Data Set ◽  
Forecast Performance ◽  
Frontier Analysis ◽  
Combination Model ◽  
Analysis Technique ◽  
Forecast Models

Forecast combination has received a great deal of attention in the tourism domain. In this article, we propose a novel performance-based tourism forecast combination model by applying a multiple-criteria decision-making framework and the stochastic frontier analysis technique to determine combination weights for individual tourism forecast models. Thirteen time-series models are used to generate individual forecast tourism models, and five competing forecast combination models are selected to evaluate the forecast performance. Using the tourism forecast competition data set, we conclude that the proposed combination model significantly and statistically outperforms the five competing combination models in most cases based on multiple performance indicators. Our results show that the proposed model offers a good solution to identify optimal weights for individual tourism forecast models.

Analysis and forecast of wildfires using Copernicus data and services

2020 ◽  
Author(s):  
Claudia Vitolo ◽  
Francesca Di Giuseppe ◽  
Mark Parrington
Keyword(s):  
R Package ◽  
Management Service ◽  
The European Union ◽  
Climate Data ◽  
Related Data ◽  
Emergency Situations ◽  
Mitigation And Adaptation ◽  
Efficient Management ◽  
Monitoring Service ◽  
State Of The Environment

<p>Copernicus is the European Union’s Earth Observation programme aiming at monitoring and forecasting the state of the environment on land, sea and in the atmosphere, in order to support climate change mitigation and adaptation strategies, the efficient management of emergency situations and improve the security of every citizen.</p><p>Copernicus has created a wealth of datasets related to the forecasting of wildfire danger as well as the detection of wildfire events and related emissions in the atmosphere. These products contribute to the operational services provided by the Copernicus Emergency Management Service (CEMS) and the Copernicus Atmosphere Monitoring Service (CAMS) and consists of real time forecasts as well as historical datasets based on ECMWF reanalysis database ERA5. Most of these data are available through the Copernicus Climate Data Store (CDS) and the Global Wildfire Information System (GWIS).</p><p>We will present the complete wildfire-related data offering under the Copernicus CDS and GWIS and showcase how data can be post-processed and visualised using the caliver R package.</p>

scholarly journals ASSESSING AND ADDRESSING CLIMATE-INDUCED RISK IN SUB-SAHARAN RAINFED AGRICULTURE: LESSONS LEARNED

2011 ◽  
Vol 47 (2) ◽  
pp. 395-410 ◽  
Author(s):  
R. COE ◽  
R. D. STERN
Keyword(s):  
Climate Change ◽  
Crop Production ◽  
Agricultural Research ◽  
Positive Impact ◽  
Central Africa ◽  
Lessons Learned ◽  
List Type ◽  
Climate Data ◽  
Seasonal Forecasts ◽  
Pastoral Systems

SUMMARYA defining characteristic of many rainfed tropical agricultural systems is their vulnerability to weather variability. There is now increased attention paid to climate-agriculture links as the world is focused on climate change. This has shown the need for increased understanding of current and future climate and the links to agricultural investment decisions, particularly farmers’ decisions, and that integrated strategies for coping with climate change need to start with managing current climate risk. Research, largely from an Association for Strengthening Agricultural Research in Eastern and Central Africa (ASARECA) project to demonstrate the value of such increased understanding, is presented in this issue of the journal. Key lessons from this research are as follows: 1.Statistical methods of analysis of historical climate data that are relevant to agriculture need not be complex. The most critical point is to describe the climate in terms of events of direct relevance to farming (such as the date of the start of a rainy season) rather than simple standard measures (such as annual total rainfall).2.Analysis requires access to relevant data, tools and expertise. Daily climate data, both current and historical, are primarily the responsibility of national meteorological services (NMS). Accessing such data, particularly daily data, is not always easy. Including staff from the NMS as research partners, not just data providers, can reduce this problem.3.Farmers’ perceptions of climate variation, risk and change are complex. They are keenly aware of variability, but there is evidence that they over-estimate risks of negative impacts and thereby fail to make use of good conditions when they occur. There is also evidence that multiple causes of changes are confounded, so farmers who observe decreasing crop production may not be distinguishing between rainfall change and declining soil fertility or other conditions. Hence any project working with farmers’ coping and adaptation to climate must also have access to analyses of observed climate data from nearby recording stations.4.Mechanisms for reducing and coping with risks are exemplified in pastoral systems that exist in the most variable environments. New approaches to risk transfer, such as index-based insurance, show potential for positive impact.5.Skilful seasonal forecasts, which give a better indication of the coming season than a simple average, would help farmers take decisions for the coming cropping season. Increasing meteorological knowledge shows that such forecasting is possible for parts of Africa. There are institutional barriers to farmers accessing and using the forecast information. Furthermore, the skill of the forecasts is currently limited so that there are maybe still only a few rational choices for a farmer to make on the basis of a forecast.With the justified current interest in climate and agriculture, all stakeholders including researchers, data providers, policy developers and extension workers will need to work together to ensure that interventions are based on a correct interpretation of a valid analysis of relevant data.

scholarly journals Model Hybrid for Sales Forecast for the Housing Market of São Paulo

2020 ◽  
Vol 28 (3) ◽  
pp. 45-64
Author(s):  
Matheus Fernando Moro ◽  
Andreas Dittmar Weise ◽  
Antonio Cezar Bornia
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Geometric Mean ◽  
Principal Component ◽  
Sao Paulo ◽  
Forecast Combination ◽  
São Paulo ◽  
Forecast Performance ◽  
Sales Forecast ◽  
Residential Units

AbstractThis research proposes a combined model of time series for forecasting housing sales in the city of São Paulo. We used data referring to the time series of sales of residential units provided by SECOVI-SP. The Exponential Softening, Box-Jenkins and Artificial Neural Networks models are individually modelled, later these are combined through five forecast combination techniques.The techniques used are Arithmetic Mean, Geometric Mean, Harmonic Mean, Linear Regression and Principal Component Analysis. The measures of accuracy to measure the results obtained and to select the best model are the RMSE, MAPE and UTheil of forecast. The results showed that Linear Regression with an independent variable, being a combination of the SARIMA model (2,0,0)(2,0,0)12 and MLP/RNA (12,10,1), provided a satisfactory performance, with an RMSE of 368.74, MAPE of 19.2% and UTheil of 0.315.The combination of time series models allowed a significant increase in forecast performance. Finally, the model was validated, using it to predict housing sales. The results show that the model has a good fit, thus demonstrating that using a housing sales forecasting model helps industry professionals minimize error and make sales and launch decisions.

scholarly journals Feed stock crop options, crop research and development strategy for bioenergy production in India

2009 ◽  
Vol 1 (1) ◽  
pp. 109-116
Author(s):  
S. Ramesh ◽  
Balakrishna Gowda
Keyword(s):  
Research And Development ◽  
Development Strategy ◽  
Fossil Fuels ◽  
Fuel Production ◽  
Public And Private ◽  
Fuel Feed ◽  
Development Interventions ◽  
Feed Stock ◽  
Potential Benefits ◽  
Crop Research

Soaring prices of fossil-fuels and environmental pollution associated with their use, has resulted in increased interest in the production and use of bio-energy in India. Government of India has made policies to promote the production and use of bio-fuels which have triggered public and private investments in bio-fuel feed stock crop research and development and bio-fuel production. In this paper, efforts have been made to review and discuss various feed stock crop options and crop research and development interventions required to generate feed-stocksto produce required volume of bio-energy to meet projected demand without compromising food/fodder security and potential benefits of bio-fuels in reducing environment pollution and contributing to the energy security in India.

scholarly journals A Forecast Combination Framework with Multi-Time Scale for Livestock Products’ Price Forecasting

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Liwen Ling ◽  
Dabin Zhang ◽  
Amin W. Mugera ◽  
Shanying Chen ◽  
Qiang Xia
Keyword(s):  
Time Scale ◽  
Geometric Mean ◽  
Forecast Combination ◽  
Short Term ◽  
Forecast Performance ◽  
Short Term Forecast ◽  
Superior Result ◽  
Combination Methods ◽  
Term Forecast ◽  
Livestock Products

China’s livestock market has experienced exceptionally severe price fluctuations over the past few years. In this paper, based on the well-established idea of “forecast combination,” a forecast combination framework with different time scales is proposed to improve the forecast accuracy for livestock products. Specifically, we combine the forecasts from multi-time scale, i.e., the short-term forecast and the long-term forecast. Forecasts derived from multi-time scale introduce complementary information about the dynamics of price movements, thus increasing the diversities within the modeling process. Moreover, we investigate a total of ten combination methods with different weighting schemes, including linear and nonlinear combination. The empirical results show that (i) forecast performance can be remarkably improved with this novel combination idea, and short-term forecast model is more suitable for the products with a relatively high volatility, e.g., mutton and beef; (ii) geometric mean, which provides a nonlinear combination, is the most effective one among all the combination methods; and (iii) variance-based weighting scheme can yield a superior result compared to the best individual forecast, especially for the products such as egg and beef.

Socioeconomics of Solidarity

2016 ◽  
pp. 192-215
Author(s):  
José Manuel Saiz-Alvarez
Keyword(s):  
Common Good ◽  
Development Aid ◽  
Economic Thought ◽  
The European Union ◽  
European Development Fund ◽  
Public And Private ◽  
Common Framework ◽  
European Development ◽  
The Common ◽  
Official Development Aid

This work deals with the Socioeconomics of Solidarity analyzed from a double public and private perspectives. The chapter begins with the guiding principles of this emerging economic thought based on the principle of subsidiarity, the search for the Common Good, and the necessary solidarity based on justice. After having grounded these principles, the author develops different solidarity-based public policies, mainly focused on the European Union, by including principles, objectives and stages of the European Official Development Aid, the European Development Fund, and the Common Framework for Joint Multiannual Programming and Efficiency. This analysis is complemented with the ideas rooted on the Socioeconomics of Solidarity that is analyzed following a private perspective, arguing that it is necessary to re-launch these School of Thought based on solidarity and justice to search for an economic world characterized by social welfare and economic wealth.

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