Evidence map›Paper›PMID 38776270›Full record

ArticlePloS one2024

Uncertainty reduction for precipitation prediction in North America.

Dan Lou, Wouter R Berghuijs, Waheed Ullah, Boyuan Zhu, Dawei Shi, Yong Hu, Chao Li, Safi Ullah, Hao Zhou, Yuanfang Chai and 1 more

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Dan LouNanjing Nriet Industrial Co., Ltd., Nanjing, China.ORCID 0000-0002-8013-1582
Wouter R BerghuijsDepartment of Earth Sciences, Free University Amsterdam, Amsterdam, Netherlands.ORCID 0000-0002-7447-0051
Waheed UllahDefense and Security, Rabdan Academy, Abu Dhabi, United Arab Emirates.
Boyuan ZhuSchool of Hydraulic Engineering, Changsha University of Science & Technology, Changsha, China.ORCID 0000-0002-7148-4511
Dawei ShiLianyungang Meteorological Bureau, Haizhou District, Lianyungang City, Jiangsu Province, P.R. China.
Yong HuState Key Laboratory of Water Resources and Hydropower Engineering Science, School of Water Resources and Hydropower Engineering, Wuhan University, Wuhan, China.
Chao LiJiangsu Meteorological Observatory, Nanjing, China.
Safi UllahDepartment of Atmosphere and Oceanic Sciences & Institute of Atmospheric Science, Fudan University, Shanghai, China.ORCID 0000-0002-2328-8321
Hao ZhouPeixian Meteorological Bureau, Jiangsu Province, China.
Yuanfang ChaiFaculty of Geographical Science, State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China.
Danyang YuDepartment of Water Resources, ITC Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Large differences in projected future annual precipitation increases in North America exists across 27 CMIP6 models under four emission scenarios. These differences partly arise from weak representations of land-atmosphere interactions. Here we demonstrate an emergent constraint relationship between annual growth rates of future precipitation and growth rates of historical temperature. The original CMIP6 projections show 0.49% (SSP126), 0.98% (SSP245), 1.45% (SSP370) and 1.92% (SSP585) increases in precipitation per decade. Combining observed warming trends, the constrained results show that the best estimates of future precipitation increases are more likely to reach 0.40-0.48%, 0.83-0.93%, 1.29-1.45% and 1.70-1.87% respectively, implying an overestimated future precipitation increases across North America. The constrained results also are narrow the corresponding uncertainties (standard deviations) by 13.8-31.1%. The overestimated precipitation growth rates also reveal an overvalued annual growth rates in temperature (6.0-13.2% or 0.12-0.37°C) and in total evaporation (4.8-14.5%) by the original models' predictions. These findings highlight the important role of temperature for accurate climate predictions, which is important as temperature from current climate models' simulations often still have systematic errors.

Indexed as

RainClimate ChangeForecastingModels, TheoreticalNorth AmericaTemperatureUncertainty

Identifiers

PMID38776270
PMCPMC11111050

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.