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Antony Millner

1. Introduction It has long been recognized that seasonal forecasts hold tremendous potential value for managing climate risks ( Mjelde et al. 1998 ; Messina et al. 1999 ; Palmer 2002 ). Despite this widely accepted assertion, relatively little of that potential value is extracted by actual forecast users ( Rayner et al. 2005 ; Vogel and O’Brien 2006 ), often despite an increase in forecast skill over the past decade ( Saha et al. 2006 ). There is growing awareness in the forecasting

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Anne C. Steinemann

1. Introduction Improvements in climate forecasts have created the potential to improve seasonal to interannual water resources management. This potential remains largely untapped, however, because forecasts are not frequently used in actual decision making. Barriers to forecast use, as noted in prior studies, include user difficulties in understanding, applying, evaluating, and trusting the forecasts ( Hartmann et al. 2002 ; Pulwarty and Redmond 1997 ; Schneider and Garbrecht 2003

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Michael K. Tippett, Anthony G. Barnston, and Shuhua Li

1. Introduction The purpose of this paper is to document the performance of a multimodel real-time ENSO forecast product over the period 2002–11. Since February of 2002, a number of groups have provided their ENSO forecasts to the International Research Institute for Climate and Society (IRI). Those forecasts are the basis for probabilistic ENSO category forecasts as well as an “ENSO prediction plume” like the one shown in Fig. 1 from February 2011. Here we limit our analysis to the ENSO

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Michael K. Tippett, Laurie Trenary, Timothy DelSole, Kathleen Pegion, and Michelle L. L’Heureux

1. Introduction “Forecast climatologies” are used in weather and climate prediction to correct systematic model errors and to express forecasts as anomalies. A forecast climatology is the expected (average) forecast value for a specified start time, lead time, and target period. The calculation of a forecast climatology is similar in many ways to that of an observational climatology, except that a forecast climatology can depend on lead time as well as target period and is computed from

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J. V. Ratnam, Takeshi Doi, Willem A. Landman, and Swadhin K. Behera

1. Introduction Most of the subsistence farmers across South Africa depend on the onset of summer rains for planting maize, the staple food of the country ( Tadross et al. 2005 ; Moeletsi et al. 2011 ). Successful long-lead forecasting of the dates of onset would be beneficial to the farmers in planning their farming activities. There have been some studies, for example, Reason et al. (2005) , Tadross et al. (2005) , and Moeletsi et al. (2011) , to understand the processes associated with

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Huixia He, Vitali E. Fioletov, David W. Tarasick, Thomas W. Mathews, and Craig Long

tropics. The scale was established from analysis of spectral UV data measured by Brewer spectrophotometers at Toronto, Ontario, Canada, between 1989 and 1992 ( Kerr and McElroy 1993 ; Kerr et al. 1994 ). In 1994 a UV index program was introduced in the United States by the National Weather Service (NWS; Long et al. 1996 ), which was replaced by the current forecast system in 2005. The UV index is now in operational use in more than 100 countries worldwide, including all of the countries of Europe

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Steven A. Mauget and Jonghan Ko

; Kiladis and Diaz 1989 ), the state of those indices also persist or develop predictably over interseasonal time scales ( Rasmusson and Carpenter 1982 ; Trenberth and Shea 1987 ). As a result, they can be used as leading indicators in simple schemes to predict seasonal climate variation. In studying the effect of ENSO-related forecast information in agricultural management such simple forecasting methods are useful because they can be easily integrated into long-term management and cropping

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Yan Guo, Jianping Li, and Yun Li

1. Introduction As one of the particular focuses of the World Climate Research Programme’s Climate Variability and Predictability (CLIVAR) project, seasonal forecasting is of great significance. Although state-of-the-art climate models have been improved significantly and have been verified to be useful tools for seasonal forecasting, their forecast skill for precipitation, especially for Asian summer monsoon precipitation, remains limited ( Wu et al. 2009 ; Lee et al. 2011 ). North China

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Joao Gari da Silva Fonseca Jr., Fumichika Uno, Hideaki Ohtake, Takashi Oozeki, and Kazuhiko Ogimoto

1. Introduction The worldwide dissemination of photovoltaic (PV) power systems in the current decade has been remarkable. Just between 2010 and 2017, the worldwide installed capacity of PV power increased from 40 to 403 GW ( International Energy Agency 2018 ). Such growth, associated with the intrinsic weather-dependent variability typical of PV power generation, has caused a strong demand for improvements in day-ahead forecasting of solar irradiation. Day-ahead forecasts of solar irradiation

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Amir Givati, Barry Lynn, Yubao Liu, and Alon Rimmer

Kinneret play a crucial role in Israeli agricultural and hydrological planning and in flood control. Hydrological forecasts are instrumental for decision-support activities at the Israel Water Authority. Major operational weather forecast centers provide relatively coarse (~16–25-km grid increment) precipitation analyses and forecasts, which are incapable of resolving the necessary details of the complex precipitation structures that are forced by mesoscale orography, land surface heterogeneities, and

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