A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

CLIMBra - Climate Change Dataset for Brazil. | LitMetric

CLIMBra - Climate Change Dataset for Brazil.

Sci Data

Department of Hydraulics and Sanitation, São Carlos School of Engineering, University of São Paulo, CxP. 359, São Carlos, São Paulo, 13566-590, Brazil.

Published: January 2023

General Circulation and Earth System Models are the most advanced tools for investigating climate responses to future scenarios of greenhouse gas emissions, playing the role of projecting the climate throughout the century. Nevertheless, climate projections are model-dependent and may show systematic biases, requiring a bias correction for any further application. Here, we provide a dataset based on an ensemble of 19 bias-corrected CMIP6 climate models projections for the Brazilian territory based on the SSP2-4.5 and SSP5-8.5 scenarios. We used the Quantile Delta Mapping approach to bias-correct daily time-series of precipitation, maximum and minimum temperature, solar net radiation, near-surface wind speed, and relative humidity. The bias-corrected dataset is available for both historical (1980-2013) and future (2015-2100) simulations at a 0.25° × 0.25° spatial resolution. Besides the gridded product, we provide area-averaged projections for 735 catchments included in the Catchments Attributes for Brazil (CABra) dataset. The dataset provides important variables commonly used in environmental and hydroclimatological studies, paving the way for the development of high-quality research on climate change impacts in Brazil.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9860025PMC
http://dx.doi.org/10.1038/s41597-023-01956-zDOI Listing

Publication Analysis

Top Keywords

climate change
8
dataset
5
climate
5
climbra climate
4
change dataset
4
dataset brazil
4
brazil general
4
general circulation
4
circulation earth
4
earth system
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!