<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="pt">
<Esri>
<CreaDate>20210408</CreaDate>
<CreaTime>19345700</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>TRUE</SyncOnce>
</Esri>
<dataIdInfo>
<idCitation>
<resTitle>Temperatura_MAX_anual_rcp4_20km_canesm</resTitle>
</idCitation>
<idAbs>O projeto GEF-CGEE-CGPDI "Estudos de projeções de clima para a Região Integrada de Desenvolvimento do Distrito Federal e Entorno – RIDE", executado pelo INPE, gerou um conjunto expressivo de dados que foram incorporados ao banco de dados geográfico do SISDIA. Contemplam dados de simulação baseados no modelo climático global CanESM2, com periodicidade mensal e anual.
O arquivo tabular contempla o padrão de resolução espacial de 20 km e apresenta valores anuais de variáveis climáticas para o cenário de simulação “Projeções futuras - Cenário RCP4.5”, para o período de 2006 a 2099:
- Precipitação Total (prec) - mm/ano;
- Temperatura a 2 metros (tp2m) - °C;
- Radiação de Onda Curta Incidente à Superfície (ocis) - W/m²;
- Temperatura Máxima a 2 m (mxtp) - °C;
- Temperatura Mínima a 2 m (mntp) - °C;
- Umidade Relativa a 2 m (ur2m) - %;
- Vento Zonal a 10 metros (u10m) - m/s;
- Vento Meridional a 10 metros (v10m) - m/s;
- Vento Zonal a 100 metros (u100) - m/s;
- Vento Meridional a 100 metros (v100) - m/s.</idAbs>
<searchKeys>
<keyword>Ambiental</keyword>
<keyword> Clima</keyword>
<keyword> Temperatura Máxima</keyword>
</searchKeys>
<idPurp>Dados anuais de temperatura máxima de projeções futuras (2006 a 2099) Cenário RCP4.5 com resolução espacial de 20 km</idPurp>
<idCredit/>
<resConst>
<Consts>
<useLimit/>
</Consts>
</resConst>
</dataIdInfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">/9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a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</Data>
</Thumbnail>
</Binary>
</metadata>
