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Atmosphere
Special Issues
Improved (Sub)Seasonal Climate Forecast for Impact Modelling
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Improved (Sub)Seasonal Climate Forecast for Impact Modelling

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: closed (31 July 2019) | Viewed by 5920

Special Issue Editor

Dr. Patrick Laux

E-Mail Website
Guest Editor
Department of Atmospheric Environmental Research (IMK-IFU), Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany
Interests: dynamical and statistical downscaling; bias correction; seasonal climate predictions; agricultural and hydrological impact assessment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Global seasonal climate forecasts (GSCFs) are being widely used to predict weather anomalies at monthly intervals and with lead times of a few months. The physical basis behind predictability at sub-seasonal to seasonal time scales (weeks to months) is given by interactions between the atmosphere and slowly varying boundary conditions of the land-surface, including the ocean surface. Examples of such variables with good predictability are sea surface temperature (SST), soil moisture, as well as snow- and ice cover.

Many potential applications exist across different sectors, such as adapted cropping schedules and irrigation demands for agriculture, potential power estimation from water- and wind for energy, and snow security for tourism.

It is also well known that the performance of the forecasts, i.e., the predictability of hydrometeorological variables, varies from region to region. Because of the need to improve the management of the available water resources for food- and energy production, as well as the high potential predictability of hydrometeorological variables for (sub-)tropical regions for the forthcoming season, the regional focus is set on semi-arid regions worldwide. Semi-arid regions are often characterized by a monsoonal climate with distinct rainy and dry seasons. This provides the potential to improve the management of the available water resources.

Since globally available products are usually too coarse to support decision making on relevant scales, this Special Issue focuses on how to improve sub-seasonal to seasonal climate forecasts for agricultural and hydrological applications on local scales. This Special Issue targets all relevant contributions on the development of regional and local seasonal climate forecasting systems such as local refinement (dynamical and statistical downscaling, as well as bias correction of GSCFs) and seasonal ensemble forecasts, improved forecast verification tools for seasonal forecast, as well as improved dissemination strategies and communication for decision-making. The collection of papers will be of interest for researchers, practitioners, and stakeholders in agriculture and water resources management.

Dr. Patrick Laux
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • global seasonal climate forecasts
  • sub-seasonal to seasonal forecasts
  • ensemble simulations
  • dynamical and statistical downscaling
  • bias correction
  • numerical weather prediction
  • forecast verification
  • decision-making
  • water resources management

Published Papers (1 paper)

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Research

21 pages, 7051 KiB  
Article
Seasonal Forecasting of the Onset of the Rainy Season in West Africa
by Manuel Rauch, Jan Bliefernicht, Patrick Laux, Seyni Salack, Moussa Waongo and Harald Kunstmann
Atmosphere 2019, 10(9), 528; https://doi.org/10.3390/atmos10090528 - 08 Sep 2019
Cited by 12 | Viewed by 5521
Abstract
Seasonal forecasts for monsoonal rainfall characteristics like the onset of the rainy seasons (ORS) are crucial for national weather services in semi-arid regions to better support decision-making in rain-fed agriculture. In this study an approach for seasonal forecasting of the ORS is proposed [...] Read more.
Seasonal forecasts for monsoonal rainfall characteristics like the onset of the rainy seasons (ORS) are crucial for national weather services in semi-arid regions to better support decision-making in rain-fed agriculture. In this study an approach for seasonal forecasting of the ORS is proposed using precipitation information from a global seasonal ensemble prediction system. It consists of a quantile–quantile-transformation for eliminating systematic differences between ensemble forecasts and observations, a fuzzy-rule based method for estimating the ORS date and graphical methods for an improved visualization of probabilistic ORS forecasts. The performance of the approach is tested for several climate zones (the Sahel, Sudan and Guinean zone) in West Africa for a period of eleven years (2000 to 2010), using hindcasts from the Seasonal Forecasting System 4 of ECMWF. We indicated that seasonal ORS forecasts can be skillful for individual years and specific regions (e.g., the Guinean coasts), but also associated with large uncertainties. A spatial verification of the ORS fields emphasizes the importance of selecting appropriate performance measures (e.g., the anomaly correlation coefficient) to avoid an overestimation of the forecast skill. The graphical methods consist of several common formats used in seasonal forecasting and a new index-based method for a quicker interpretation of probabilistic ORS forecast. The new index can also be applied to other seasonal forecast variables, providing an important alternative to the common forecast formats used in seasonal forecasting. Moreover, the forecasting approach proposed in this study is not computationally intensive and is therefore operational applicable for forecasting centers in tropical and subtropical regions where computing power and bandwidth are often limited. Full article
(This article belongs to the Special Issue Improved (Sub)Seasonal Climate Forecast for Impact Modelling)
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