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: 3122
Function: getPubMedXML

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

Future precipitation and near surface air-temperature projection using CMIP6 models based on TOPSIS method: case study, Sistan-and-Baluchestan Province of Iran. | LitMetric

Based on surface air temperature and precipitation, the current study examines the climate fluctuations over Sistan-and-Baluchestan Province, Iran's second-largest province. This area suffers from insufficient direct observations and a lack of climatic investigation. Three datasets were utilized including in situ data, gridded data (1984-2013), outputs of historical runs (during 1984-2013), and projections under the SSP5-8.5, SSP3-7.0, and SSP1-2.6 scenarios (in 2020-2049) of twenty-six Global Climate Models (GCMs) from the latest Coupled Model Intercomparison Project (CMIP6). The models' performance has been evaluated and ranked using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) in Multi-Criteria Decision Making (MCDM) technique including eight metrics in both seasonal and annual scales. The surface air temperature showed an increasing trend in seasonal and annual scales during 1984-2013, while the monthly precipitation trend increased for September-October-November and decreased for the other seasons and annual scale during 1984-2013. The top-ranked models for simulating surface air temperature (precipitation) were CESM2 (GFDL-ESM4), IPSL-CM6A-LR (UKESM1-0-LL), ACCESS-CM2 (GFDL-ESM4), and MIROC-ES2L (MPI-ESM1-2-LR) models in DJF, MAM, JJA, and SON seasons, respectively, while ACCESS-CM2 (CNRM-CM6-1-HR) model outperformed others in annual scale. Bias-corrected outputs of the top-ranked CMIP6 GCMs showed an increasing trend for surface air temperature in all seasons (from a 0.7 K increase in December-January-February season under SSP3-7.0 scenario to a 2.5 K increase in June-July-August season under SSP5-8.5 scenario) for period 2020-2049, comparing with that in 1984-2013 period. Bias-corrected monthly precipitation projected by top-ranked CMIP6 GCMs indicated both increasing and decreasing trends depending on selected season and scenario. This varied from a 5 mm/month decrease within December-January-February season under SSP5-8.5 scenario to a 13 mm/month increase during the March-April-May season under SSP1-2.6 scenario in 2020-2050, comparing with that from previous years.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s10661-023-12084-xDOI Listing

Publication Analysis

Top Keywords

surface air
16
air temperature
16
sistan-and-baluchestan province
8
temperature precipitation
8
seasonal annual
8
annual scales
8
increasing trend
8
monthly precipitation
8
annual scale
8
top-ranked cmip6
8

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!