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The joint WWRP–WCRP Subseasonal to Seasonal Prediction Project (e.g., Robertson et al. 2014) created a global repository of experimental or operational near-real-time S2S forecasts and reforecasts (hindcasts) from 11 international meteorological institutions, cohosted by ECMWF and CMA (Vitart et al. 2017). These data are publicly accessible by researchers and users (https://apps.ecmwf.int/datasets/data/s2s and http://s2s.cma.cn/index). With the exception of the fourth case study, which uses GloSea5 forecasts (MacLachlan et al. 2015), all case studies use selected S2S forecasts and reforecasts that are available from this repository, providing a consistent basis for S2S forecast skill assessment and evaluation of their utility. The subseasonal-to-seasonal (S2S) predictive time scale, encompassing lead times ranging from 2 weeks to a season, is at the frontier of forecasting science. Forecasts on this time scale provide opportunities for enhanced application-focused capabilities to complement existing weather and climate services and products. There is, however, a “knowledge–value” gap, where a lack of evidence and awareness of the potential socioeconomic benefits of S2S forecasts limits their wider uptake. To address this gap, here we present the first global community effort at summarizing relevant applications of S2S forecasts to guide further decision-making and support the continued development of S2S forecasts and related services. Focusing on 12 sectoral case studies spanning public health, agriculture, water resource management, renewable energy and utilities, and emergency management and response, we draw on recent advancements to explore their application and utility. These case studies mark a significant step forward in moving from potential to actual S2S forecasting applications. We show that by placing user needs at the forefront of S2S forecast development—demonstrating both skill and utility across sectors—this dialogue can be used to help promote and accelerate the awareness, value, and cogeneration of S2S forecasts. We also highlight that while S2S forecasts are increasingly gaining interest among users, incorporating probabilistic S2S forecasts into existing decision-making operations is not trivial. Nevertheless, S2S forecasting represents a significant opportunity to generate useful, usable, and actionable forecast applications for and with users that will increasingly unlock the potential of this forecasting time scale. DD gratefully acknowledges support from the Swiss National Science Foundation through project PP00P2_170523. For case study 1, ACP and WTKH were funded by the U.K. Climate Resilience Programme, supported by the UKRI Strategic Priorities Fund. RWL was funded by NERC Grant NE/P00678/1 and by the BER DOE Office of Science Federal Award DE-SC0020324. TS was funded by NERC Independent Research Fellowship (NE/P018637/1). CMG and DB were funded by the Helmholtz Young Investigator Group “SPREADOUT” Grant VH-NG-1243. Case study 2 was supported by the U.K. Global Challenges Research Fund NE/P021077/1 (GCRF African SWIFT) and the Tertiary Education Trust Fund (TETFUND) of Nigeria TETFund/DR&D/CE/NRF/STI/73/VOL.1. EO thanks Adrian Tomkins of ICTP, Italy, for his contribution. Case study 3 was undertaken as part of the Columbia World Project, ACToday, Columbia University (https://iri.columbia.edu/actoday/). Case study 4 was supported by the ForPAc (Towards Forecast-based Preparedness Action) project within the NERC/FCDO SHEAR Programme NE/P000428/1, NE/P000673/1, and NE/P000568/1. Case study 5 was undertaken as part of the International Research Applications Project, funded by the U.S. National Oceanic and Atmospheric Administration. EO thanks IRAP project colleagues at The University of Arizona, Indian Meteorological Department, Regional Integrated Multi-Hazard Early Warning System for Africa and Asia, and two of Bihar’s State Agricultural Universities for their contributions. For case study 6, CASC thanks Conselho Nacional de Desenvolvimento Científico e Tecnológico Process 305206/2019-2 and Fundação de Amparo à Pesquisa do Estado de São Paulo Process 2015/50687-8 (CLIMAX Project) for their support. For case study 7, DW’s contributions were carried out under contract with the National Aeronautics and Space Administration. Case study 8 was funded by the EU Horizon 2020 Research and Innovation Programme Grant 7767874 (S2S4E). We also acknowledge the Subseasonal-to-Seasonal Project’s Real-Time Pilot Initiative for providing access to real-time forecasts. For case study 9, TIC-LCPE Hydro-04 was funded by the University of Strathclyde’s Low Carbon Power and Energy program. JB was supported by EPSRC Innovation Fellowship EP/R023484/1. We thank Andrew Low and Richard Hearnden from SSE Renewables for their input. Case study 10 was supported by the Earth Systems and Climate Change Hub under the Australian Government’s National Environmental Science Program, and the Decadal Climate Forecasting Project (CSIRO). Case study 11 was funded by the Technologies for Sustainable Built Environments Centre, Reading University, in conjunction with the EPSRC Grant EP/G037787/1 and BT PLC. Case study 12 was funded through the framework service contract for operating the EFAS Computational Center Contract 198702 and the Copernicus Fire Danger Computations Contract 389730 295 in support of the Copernicus Emergency Management Service and Early Warning Systems between the Joint Research Centre and ECMWF. Peer Reviewed "Article signat per 60 autors/es: Christopher J. White, Daniela I. V. Domeisen, Nachiketa Acharya, Elijah A. Adefisan, Michael L. Anderson, Stella Aura, Ahmed A. Balogun, Douglas Bertram, Sonia Bluhm, David J. Brayshaw, Jethro Browell, Dominik Büeler, Andrew Charlton-Perez, Xandre Chourio, Isadora Christel, Caio A. S. Coelho, Michael J. DeFlorio, Luca Delle Monache, Francesca Di Giuseppe, Ana María García-Solórzano, Peter B. Gibson, Lisa Goddard, Carmen González Romero, Richard J. Graham, Robert M. Graham, Christian M. Grams, Alan Halford, W. T. Katty Huang, Kjeld Jensen, Mary Kilavi, Kamoru A. Lawal, Robert W. Lee, David MacLeod, Andrea Manrique-Suñén, Eduardo S. P. R. Martins, Carolyn J. Maxwell, William J. Merryfield, Ángel G. Muñoz, Eniola Olaniyan, George Otieno, John A. Oyedepo, Lluís Palma, Ilias G. Pechlivanidis, Diego Pons, F. Martin Ralph, Dirceu S. Reis Jr., Tomas A. Remenyi, James S. Risbey, Donald J. C. Robertson, Andrew W. Robertson, Stefan Smith, Albert Soret, Ting Sun, Martin C. Todd, Carly R. Tozer, Francisco C. Vasconcelos Jr., Ilaria Vigo, Duane E. Waliser, Fredrik Wetterhall, and Robert G. Wilson"

Resumo O presente artigo faz uma revisão bibliográfica e aborda os principais índices utilizados no monitoramento e análise de secas. Além disso, o texto ainda discorre sobre as metodologias empregadas mundialmente no monitoramento e previsão desses eventos. As secas ocorrem quando existe um déficit de precipitação comparado à média histórica da região. Elas podem ser diagnosticadas por meio de índices que identificam os períodos de escassez ou de disponibilidade hídrica através de equações. Dessa forma, é possível determinar a intensidade, frequência e duração dos eventos de seca. Nesse âmbito, alguns países implementaram seus próprios sistemas de monitoramento e alerta precoce das secas como o Monitor de Secas dos Estados Unidos, o Monitor de Secas da Europa e o Monitor de Secas do Brasil. Onde estes, utilizam de forma conjunta ou isolada as informações provenientes dos índices, a fim de identificar e caracterizar os eventos de seca. Desse modo, pode haver um melhor planejamento das instituições responsáveis, adoção de planos emergenciais e mitigação de impactos. Abstract The present work is a bibliographic review and addresses the main indexes used in the monitoring and analysis of droughts. In addition, the text also discusses the methodologies utilized worldwide in monitoring and forecasting these events. Droughts occur when there is a rainfall deficit compared to the region's historical average. They can be diagnosed by means of indices that identify periods of scarcity or availability hydric through equations. In this way, it is possible to determine the intensity, frequency, and duration of drought events. In this context, some countries have implemented their own drought monitoring and early warning systems such as the United States Drought Monitor, Europe's Drought Monitor and Brazil's Drought Monitor. Where they use information from indexes together or in isolation, in order to identify and characterize drought events. Thus, there can be better planning by the responsible institutions, adoption of emergency plans and mitigation of impacts.

International audience; The semi-arid Northeast Brazil (NEB) is just recovering from a very severe water crisis induced by a multiyear drought. With this crisis, the question of water resources management has entered the national political agenda, creating an opportunity to better prepare the country to deal with future droughts. In order to improve climate predictions, and thus preparedness in NEB, a circulation pattern (CP) classification algorithm offers various options. Therefore, the main objective of this study was to develop a computer aided CP classification based on the Simulated ANnealing and Diversified RAndomization clustering (SANDRA) algorithm. First, suitable predictor variables and cluster domain setting are evaluated using ERA-Interim reanalyses. It is found that near surface variables such as geopotential at 1,000 hPa (GP(1,000)) or mean sea level pressure (MSLP) should be combined with horizontal wind speed at the upper 700 hPa level (UWND700). A 11-cluster solution is favoured due to the trade-offs between interpretability of the cluster centroids and the explained variances of the predictors. Second, occurrence and transition probabilities of this 11-cluster solution of GP(1,000) and UWND700 are analysed, and typical CPs, which are linked to dry and wet conditions in the region are identified. The suitability of the new classification to be potentially applied for statistical downscaling or CP-conditional bias correction approach is analysed. The CP-conditional cumulative density functions (CDFs) exhibit discriminative power to separate between wet and dry conditions, indicating a good performance of the CP approach.

Resumo O Nordeste do Brasil apresenta acentuada variabilidade interanual da precipitação com alguns anos secos e outros chuvosos. Nessa região, ocorrem os veranicos, que são dias consecutivos com ausência de precipitação durante o período da estação chuvosa, que ocasionam perdas nas safras agrícolas. O presente artigo tem como objetivo utilizar um indicador de veranicos já estabelecido por outros autores e identificar sua relação com o índice de Distribuição de Chuva e regionalizar de acordo com as macrorregiões do estado, bem como, compreender as possíveis consequências, de forma qualitativa e quantitativa, sobre as perdas de safra no Ceará. A área de estudo compreendeu o estado do Ceará e as análises foram realizadas para o período de 1980 a 2018.A partir dos dados de rendimento do IBGE, foram calculadas as perdas das culturas do milho e feijão, e através dos resultados pode-se inferir que: as correlações realizadas com os dados de perdas de safra, veranicos e o IDC evidenciaram que para a maior parte do estado existe correlação direta, ou seja, quanto maior a frequência de eventos de veranicos maior a perda de safra. Além disso, verificou-se que, quando há uma melhor distribuição da precipitação ao longo das regiões do estado ocorre menor perda de safra. Abstract Northeastern Brazil has marked interannual rainfall variability with some dry and other rainy years. In this region, there are dry spells, which are consecutive days with no rainfall during the rainy season, causing losses in agricultural crops. This article aims to use an indicator of Indian summers already established by other authors 2020 and identify its relationship with the Rain Distribution Index and regionalize according to the state's macro-regions, as well as understand the possible consequences, in a qualitative and quantitative way. on crop losses in Ceará. The study area comprised the state of Ceará and the analyzes were carried out for the period from 1980 to 2018. From the IBGE yield data, the losses of corn and beans crops were calculated, and through the results it can be inferred that: the correlations made with data on crop losses, summer and the IDC showed that for the largest part of the state there is a direct correlation, that is, the higher the frequency of summer events, the greater the crop loss. In addition, it was found that when there is a better distribution of precipitation over the regions of the state, less crop loss occurs.

Resumo Os veranicos são caracterizados como a ocorrência de dias consecutivos com ausência de precipitação na estação chuvosa, que ocasionam perdas nas safras agrícolas. O presente artigo tem como objetivo classificar e regionalizar os veranicos que ocorrem durante a estação chuvosa, bem como, compreender as possíveis consequências sobre as perdas de safra. A área de estudo foi o estado Ceará, no qual os veranicos foram definidos como três ou mais dias consecutivos com precipitação diária igual ou inferior a 2 mm. A partir dos dados de rendimento do IBGE, foram calculadas as perdas do cultivo do milho e feijão, e através dos resultados pode-se inferir que: no ano considerado chuvoso (2009), foi verificada uma menor quantidade de ocorrências de veranicos, porém com perdas de safra significativas pelo excesso de chuvas, principalmente nas porções do Litoral de Fortaleza e Litoral do Pecém. Na análise dos anos secos (1998 e 2012), verificou-se maior ocorrência de veranicos e as perdas de safras ainda mais intensas, o indicador de veranicos apresentou menores ocorrências de eventos no noroeste do estado. Os resultados indicam um provável indicador para classificar as consequências de uma estiagem na produção agrícola de sequeiro. Abstract The dry spells are characterized as the occurrence of consecutive days with no precipitation in the rainy season, which causes losses in agricultural crops. The present article aims to classify and regionalize the dry spells that occur during the rainy season, as well as to understand the possible consequences on crop losses. The study area was the state of Ceará, in which dry spells was defined as three or more consecutive days with daily precipitation equal to or less than 2 mm. From the IBGE yield data, it was calculated how the cultivation of corn and beans and the results can be inferred that: in the year considered rainy (2009), there was a smaller number of dry spells occurrences, but with losses significant crop losses due to excessive rainfall, mainly in the portions of the Litoral de Fortaleza and Litoral do Pecém. In the analysis of the dry years (1998 and 2012), there was a higher occurrence of dry spells and the losses of harvests even more intense, the dry spells indicator showed lower occurrences of events in the northwest of the state. The results indicate a probable indicator for classifying the consequences of a drought on rainfed agricultural production.

Resumo O artigo investiga como eventos de El Niño de diferentes durações afetam a circulação atmosférica no Atlântico Tropical Norte (ATN), quais consequências dessas alterações sobre a variabilidade interanual da temperatura da superfície do mar (TSM) na região e qual a resposta, em termos de anomalias de precipitação, sobre o Ceará. A análise foi feita através da composição de variáveis oceanográficas e atmosféricas para 18 eventos de El Niño, divididos em eventos de curta e longa duração. Os resultados mostram que os eventos de maior duração resultaram em anomalias positivas de TSM sobre a região do ATN, favorecendo, assim, ao desenvolvimento do gradiente inter-hemisférico de anomalias de TSM positivo e um regime de precipitação abaixo da média no Ceará. Por outro lado, as alterações na circulação atmosférica sobre o ATN não se mostraram tão intensas nos anos em que o El Niño apresentou menor duração, resultando em anomalias de TSM no ATN próximas a zero e consequentemente não foi observado um gradiente de anomalias de TSM no Atlântico Tropical. A composição das anomalias de precipitação sobre o Ceará próximas de zero nesses anos condiz com essa não formação de um gradiente de anomalias de TSM. Abstract This paper investigates how El Niño events of different durations affect the atmospheric circulation over the Tropical North Atlantic (TNA) region, what are the consequences of these alterations in the sea surface temperature (SST) interannual variability and what are the responses, in terms of precipitation anomalies, over Ceará. Composite analyses of oceanographic and atmospheric variables were made for 18 El Niño years, divided between events of short and long duration. Events that lasted longer resulted in positive SST anomalies in the TNA region, leading to an interhemispheric gradient of SST anomalies in the Tropical Atlantic and below normal precipitation anomalies over Ceará. On the other hand, the alterations in the atmospheric circulation on TNA, during years of short duration El Niño, have not shown to be as intense as those in years of long duration El Niño. This resulted in SST anomalies on TNA close to zero and consequently, the interhemispheric gradient of SST anomalies was not observed. The near normal precipitation anomalies composites are consistent with the no formation of a SST anomalies gradient.

The teleconnection between the Atlantic Niño and the Pacific El Niño Southern Oscillation (ENSO) is revisited using obser-vational and reanalysis data for the 1905-2014 period. Two types of Atlantic Niño are significantly negatively correlated with ENSO, with Atlantic leading ENSO by 6-month to 1-year. The first one is the already well-known connection between the boreal summer Atlantic Niño (ATL3: 3° N-3° S, 20° W-0°) and the subsequent winter ENSO (Niño3: 5° N-5° S, 150° W-90° W). This relationship is strong in the first and last decades of the study period. It is shown that a second Atlantic Niño in boreal fall/early winter (October-December, here in after called winter Atlantic Niño) is also significantly correlated with the following year ENSO. This winter Atlantic Niño leads to an early development of ENSO from boreal summer onwards, with a marked multidecadal modulation of the lead time. A nearly 1-year leading connection between winter Atlantic Niño and the following ENSO is generally observed in the mid-twentieth century, mostly when the summer Atlantic Niño teleconnection with the subsequent winter ENSO is weak. The same mechanism of the Atlantic-Pacific Niño connection, which involves the Walker circulation, operates for the two types of Atlantic Niño. Our analysis supports the leading influence of the summer and winter Atlantic equatorial modes on climate variability in South America. These results suggest the relevance of different types of Atlantic Niño for the 6-month to 1-year predictability of ENSO and its climatic impacts.

This sixth edition of explaining extreme events of the previous year (2016) from a climate perspective is the first of these reports to find that some extreme events were not possible in a preindustrial climate. The events were the 2016 record global heat, the heat across Asia, as well as a marine heat wave off the coast of Alaska. While these results are novel, they were not unexpected. Climate attribution scientists have been predicting that eventually the influence of human-caused climate change would become sufficiently strong as to push events beyond the bounds of natural variability alone. It was also predicted that we would first observe this phenomenon for heat events where the climate change influence is most pronounced. Additional retrospective analysis will reveal if, in fact, these are the first events of their kind or were simply some of the first to be discovered. Last year, the editors emphasized the need for additional papers in the area of “impacts attribution” that investigate whether climate change’s influence on the extreme event can subsequently be directly tied to a change in risk of the socio-economic or environmental impacts. Several papers in this year’s report address this challenge, including Great Barrier Reef bleaching, living marine resources in the Pacific, and ecosystem productivity on the Iberian Peninsula. This is an increase over the number of impact attribution papers than in the past, and are hopefully a sign that research in this area will continue to expand in the future. Other extreme weather event types in this year’s edition include ocean heat waves, forest fires, snow storms, and frost, as well as heavy precipitation, drought, and extreme heat and cold events over land. There were a number of marine heat waves examined in this year’s report, and all but one found a role for climate change in increasing the severity of the events. While humancaused climate change caused China’s cold winter to be less likely, it did not influence U.S. storm Jonas which hit the mid-Atlantic in winter 2016. As in past years, the papers submitted to this report are selected prior to knowing the final results of whether human-caused climate change influenced the event. The editors have and will continue to support the publication of papers that find no role for human-caused climate change because of their scientific value in both assessing attribution methodologies and in enhancing our understanding of how climate change is, and is not, impacting extremes. In this report, twenty-one of the twenty-seven papers in this edition identified climate change as a significant driver of an event, while six did not. Of the 131 papers now examined in this report over the last six years, approximately 65% have identified a role for climate change, while about 35% have not found an appreciable effect. Looking ahead, we hope to continue to see improvements in how we assess the influence of human-induced climate change on extremes and the continued inclusion of stakeholder needs to inform the growth of the field and how the results can be applied in decision making. While it represents a considerable challenge to provide robust results that are clearly communicated for stakeholders to use as part of their decision-making processes, these annual reports are increasingly showing their potential to help meet such growing needs.

Intraseasonal oscillations are factors controlling the interannual variability of tropical rainfall. The knowledge of how numerical models reproduce its variability is important to better understand their roles and support operations of weather and climate. This paper investigates the sensitivity of a downscaling dynamic precipitation model in predicting the intraseasonal oscillations observed in the northern sector of Northeast Brazil (SNNEB - 45°W-37o W and 2o S-12°S) during the period from 1974 to 2000. The results showed that rainfall was simulated on SNNEB explained more than 70% of the variability of rainfall observed in the quarter February to April in this region. Statistical of averages, standard deviations and percent this quarter, in this region in years of climatic contrasts in the Oceans Pacific and Atlantic Tropical were also well captured by the precipitation simulated by downscaling. Spectral analysis with the use of wavelets showed that dynamic downscaling has the potential to reproduce observed spectral peaks of precipitation in SNNEB scales up to 8 days and the scales between 64 and 128 days for the period January 1 to June 30. Keywords: Intraseasonal rainfall, wavelets, spectral analysis. Oscilações intrassazonais são fatores controladores da variabilidade pluviométrica interanual de áreas tropicais. O conhecimento de como os modelos numéricos reproduzem suas variabilidades é importante para entender melhor suas atuações e subsidiar operações de previsão de tempo e clima. Neste artigo investiga-se a sensibilidade de um modelo de downscaling dinâmico de precipitação na reprodução das oscilações intrassazonais observadas no setor norte do Nordeste do Brasil (SNNEB - 45ºW-37ºW e 2ºS-12ºS) no período de 1974 a 2000. Os resultados mostraram que a precipitação simulada sobre o SNNEB explicou aproximadamente 70% da variabilidade da precipitação observada no trimestre fevereiro a abril nesta região. Estatísticas de médias, desvios normalizados e percentuais neste trimestre, nessa região, em anos de contrastes climáticos nos Oceanos Pacífico e Atlântico Tropicais, também foram bem capturadas pela precipitação simulada através do downscaling. Análises espectrais com uso de ondeletas mostraram que o downscaling dinâmico tem potencial para reproduzir picos espectrais de precipitação observada no SNNEB nas escalas acima de 8 dias, e nas escalas entre 64 e 128 dias para o período de 01 de janeiro a 30 de junho.

Large portions of Brazil′s Northeast have experienced an intense and prolonged drought for the majority of 2010–2013. This drought, along with other droughts that have hit the South in recent years, has sparked a new round of discussions to improve drought policy and management at the federal and state levels. To assist with these efforts, the World Bank recently conducted a series of evaluations on national and sub-national drought preparedness measures and approaches across five country case studies. This particular article presents the Brazilian case study. The work draws from interviews with key experts and stakeholders, as well as document analyses, and focuses on preparedness measures and approaches at the national and one sub-national case; the state of Ceara. The analysis shows that although there is a rich history of drought management throughout Brazil, there are short-term and long-term gaps and opportunities on which decision makers might consider focusing to improve monitoring, forecasting, and early warning systems, vulnerability/resilience and impact assessments, and mitigation and response planning measures.