The state of the art and fundamental aspects of regional climate modeling in South America

Ambrizzi, Tércio; Reboita, Michelle Simões; Rocha, Rosmeri Porfírio da; Llopart, Marta

doi:10.1111/nyas.13932

Cited by 91 publications

(82 citation statements)

References 135 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In summary, the results vary with regions, however, model projections indicate that the response of precipitation variability due to global warming could be substantially increased in most of the sub‐regions (Figure 5), leading to an increase in extremes over the coming century (Figure 3). This is consistent with previous research showing projected hydroclimatic changes (Junquas et al ., 2012; Collins et al ., 2013; Hegerl et al ., 2015; Ambrizzi et al ., 2019) which can have multiple and significant impacts on the hydrological cycle and a variety of sectors (Magrin et al ., 2014).…”

Section: Resultsmentioning

confidence: 99%

“…Nevertheless, on average, the models largely agree on a precipitation decrease in much of Amazonia and Northeast Brazil in the future. They also agree on increased precipitation in southern Brazil around La Plata basin (Malhi et al ., 2009; Chou et al ., 2014a, 2014b; Ambrizzi et al ., 2019), while there are more uncertainties over the South America Monsoon region.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Assessment of rainfall variability and future change in Brazil across multiple timescales

Alves

Chadwick

Moise

et al. 2020

Intl Journal of Climatology

View full text Add to dashboard Cite

Rainfall variability change under global warming is a crucial issue that may have a substantial impact on society and the environment, as it can directly impact biodiversity, agriculture, and water resources. Observed precipitation trends and climate change projections over Brazil indicate that many sectors of society are potentially highly vulnerable to the impacts of climate change. The purpose of this study is to assess model projections of the change in rainfall variability at various temporal scales over sub-regions of Brazil. For this, daily data from 30 CMIP5 models for historical (1900-2005) and future (2050-2100) experiments under a high-emission scenario are used. We assess the change in precipitation variability, applying a band-pass filter to isolate variability on daily, weekly, monthly, intra-seasonal, and El Nino Southern Oscillation (ENSO) time scales. For historical climate, simulated precipitation is evaluated against observations to establish model reliability. The results show that models largely agree on increases in variability on all timescales in all subregions, except on ENSO timescales where models do not agree on the sign of future change. Brazil will experience more rainfall variability in the future that is, drier or more frequent dry periods and wetter wet periods on daily, weekly, monthly, and intra-seasonal timescales, even in sub-regions where future changes in mean rainfall are currently uncertain. This may provide useful information for climate change adaptation across, for example, the agriculture and water resource sectors in Brazil.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessment of rainfall variability and future change in Brazil across multiple timescales

Alves

Chadwick

Moise

et al. 2020

Intl Journal of Climatology

View full text Add to dashboard Cite

show abstract

“…Estudos sobre mudanças climáticas e o impacto na disponibilidade hídrica podem ser realizados com saídas de modelos climáticos regionais e globais, sendo que os regionais possuem capacidade de representar as circulações de mesoescala, como as brisas, o que não ocorre com os modelos climáticos globais, cuja resolução horizontal é mais grosseira. Portanto, os modelos regionais podem representar melhor o clima de uma dada região (AMBRIZZI et al, 2018). Estudos de projeções climáticas realizados para Minas Gerais utilizando saídas de ambos os modelos apontam alterações nos campos médios sazonais de precipitação e temperatura do ar (SANTOS et al, 2017;REBOITA et al, 2018a;TAVARES et al, 2018).…”

Section: Introductionunclassified

Balanço Hídrico Climatológico Para Itajubá-Mg: Cenário Atual E Projeções Climáticas

Alves¹,

Martins²,

Reboita³

2021

RBClima

Self Cite

View full text Add to dashboard Cite

Projeções climáticas ao longo do século XXI têm indicado aumento da temperatura do ar, e irregularidades na precipitação no Estado de Minas Gerais (MG), os quais afetarão a evapotranspiração e, consequentemente, o balanço hídrico. Dessa forma, o objetivo desse trabalho foi verificar o impacto das mudanças climáticas no balanço hídrico climatológico (BHC) no município de Itajubá no período de 2021 a 2099 considerando o cenário de emissão Representative Concentration Pathway (RCP) 8.5 do Intergovernmental Panel on Climate Change (IPCC). Neste estudo, foram utilizadas projeções do modelo climático regional RegCM4 dirigido pelas saídas do modelo global HadGEM2-ES. O BHC foi calculado para o clima presente (1979 – 2005), futuro próximo (2021 – 2049) e futuro distante (2071 – 2099), considerando o método de Thornthwaite e Mather simplificado, em que considera como dado de entrada a climatologia mensal da temperatura média do ar e da precipitação. Projeta-se, no final do século XXI, um aumento de aproximadamente 5ºC na temperatura média do ar para Itajubá, além de um padrão heterogêneo de precipitação, com projeções de aumento nos meses de primavera e verão e redução nos meses de outono e inverno. Para o BHC é projetado aumento gradual na evapotranspiração real, chegando a 86 mm mês-1 nos meses de verão, e alteração na deficiência (DEF) e excedente hídrico (EXC). De maneira geral, é projetado um aumento da DEF e EXC nos meses de outono, inverno e verão, respectivamente. Tais alterações podem acarretar prejuízos para os principais cultivos de Itajubá, como o milho, a batata, o feijão e o café.

show abstract

“…This work builds on previous studies which evaluated the skill of representing the climate over individual domains (e.g. Europe [28], Africa [29], South America [30]) using multi-models ensembles. The skill of the model is quantified by using probability density functions (PDF) of the observed and simulated temperature and precipitation aggregated at each climate type and each region following the PDF skill score method [31].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of New CORDEX Simulations Using an Updated Köppen–Trewartha Climate Classification

et al. 2019

View full text Add to dashboard Cite

A new ensemble of climate and climate change simulations covering all major inhabited regions with a spatial resolution of about 25 km, from the WCRP CORDEX COmmon Regional Experiment (CORE) Framework, has been established in support of the growing demands for climate services. The main objective of this study is to assess the quality of the simulated climate and its fitness for climate change projections by REMO (REMO2015), a regional climate model of Climate Service Center Germany (GERICS) and one of the RCMs used in the CORDEX-CORE Framework. The CORDEX-CORE REMO2015 simulations were driven by the ECMWF ERA-Interim reanalysis and the simulations were evaluated in terms of biases and skill scores over ten CORDEX Domains against the Climatic Research Unit (CRU) TS version 4.02, from 1981 to 2010, according to the regions defined by the Köppen–Trewartha (K–T) Climate Classification types. The REMO simulations have a relatively low mean annual temperature bias (about ± 0.5 K) with low spatial standard deviation (about ± 1.5 K) in the European, African, North and Central American, and Southeast Asian domains. The relative mean annual precipitation biases of REMO are below ± 50 % in most domains; however, spatial standard deviation varies from ± 30 % to ± 200 %. The REMO results simulated most climate types relatively well with lowest biases and highest skill score found in the boreal, temperate, and subtropical regions. In dry and polar regions, the REMO results simulated a relatively high annual biases of precipitation and temperature and low skill. Biases were traced to: missing or misrepresented processes, observational uncertainty, and uncertainties due to input boundary forcing.

show abstract

The state of the art and fundamental aspects of regional climate modeling in South America

Cited by 91 publications

References 135 publications

Assessment of rainfall variability and future change in Brazil across multiple timescales

Assessment of rainfall variability and future change in Brazil across multiple timescales

Balanço Hídrico Climatológico Para Itajubá-Mg: Cenário Atual E Projeções Climáticas

Evaluation of New CORDEX Simulations Using an Updated Köppen–Trewartha Climate Classification

Contact Info

Product

Resources

About