scholarly journals Attributing of global evapotranspiration trends based on the Budyko framework

2022 ◽  
Author(s):  
Shijie Li ◽  
Guojie Wang ◽  
Chenxia Zhu ◽  
Jiao Lu ◽  
Waheed Ullah ◽  
...  
Keyword(s):  
Linear Trend ◽  
Critical Role ◽  
Vapour Pressure Deficit ◽  
Hydrological Process ◽  
Net Radiation ◽  
Tropical Regions ◽  
Essential Variable ◽  
Multiple Datasets ◽  
Dry Climates ◽  
Substantial Control

Abstract. Actual evapotranspiration (ET) is an essential variable in the hydrological process, linking the carbon, water, and energy cycles. Global ET has significantly changed in the warming climate. Although increasing vapour pressure deficit (VPD) due to global warming enhances atmospheric water demand, it remains unclear how the dynamics of ET are affected. In this study, using multiple datasets, we disentangled the relative contributions of precipitation, net radiation, air temperature (T1), VPD, and wind speed on affecting annual ET linear trend using an advanced separation method that considers the Budyko framework. It is found that the precipitation variability dominantly controls global ET in the dry climates, the net radiation has substantial control over ET in the tropical regions, and VPD is impacting ET trends in boreal mid-latitude climate. The critical role of VPD in controlling ET trends is particularly emphasized due to its influence in controlling the land-atmosphere interactions.

Twelfth Century AD

2017 ◽  
Author(s):  
Lonnie G. Thompson ◽  
Alan L. Kolata
Keyword(s):  
Climate Change ◽  
Southern Oscillation ◽  
Sediment Cores ◽  
Critical Role ◽  
Lake Titicaca ◽  
Independent Evidence ◽  
Tropical Regions ◽  
Ice Cap ◽  
Paleoclimate Records ◽  
Past Climate Change

Climate is a fundamental and independent variable of human existence. Given that 50 percent of the Earth’s surface and much of its population exist between 30oN and 30oS, paleoenvironmental research in the Earth’s tropical regions is vital to our understanding of the world’s current and past climate change. Most of the solar energy that drives the climate system is absorbed in these regions. Paleoclimate records reveal that tropical processes, such as variations in the El Niño-Southern Oscillation (ENSO), have affected the climate over much of the planet. Climatic variations, particularly in precipitation and temperature, play a critical role in the adaptations of agrarian cultures located in zones of environmental sensitivity, such as those of the coastal deserts, highlands, and altiplano of the Andean region. Paleoclimate records from the Quelccaya ice cap (5670 masl) in highland Peru that extend back ~1800 years show good correlation between precipitation and the rise and fall of pre-Hispanic civilizations in western Peru and Bolivia. Sediment cores extracted from Lake Titicaca provide independent evidence of this correspondence with particular reference to the history of the pre-Hispanic Tiwanaku state centered in the Andean altiplano. Here we explore, in particular, the impacts of climate change on the development and ultimate dissolution of this altiplano state.

scholarly journals Multi-Zone Unit for Recurrent Neural Networks

2020 ◽  
Vol 34 (04) ◽  
pp. 5150-5157
Author(s):  
Fandong Meng ◽  
Jinchao Zhang ◽  
Yang Liu ◽  
Jie Zhou
Keyword(s):  
Neural Networks ◽  
Recurrent Neural Networks ◽  
Critical Role ◽  
Transition Function ◽  
Learning Problems ◽  
Arbitrary Length ◽  
Transition Functions ◽  
Multiple Datasets ◽  
Analysis Task ◽  
Hidden States

Recurrent neural networks (RNNs) have been widely used to deal with sequence learning problems. The input-dependent transition function, which folds new observations into hidden states to sequentially construct fixed-length representations of arbitrary-length sequences, plays a critical role in RNNs. Based on single space composition, transition functions in existing RNNs often have difficulty in capturing complicated long-range dependencies. In this paper, we introduce a new Multi-zone Unit (MZU) for RNNs. The key idea is to design a transition function that is capable of modeling multiple space composition. The MZU consists of three components: zone generation, zone composition, and zone aggregation. Experimental results on multiple datasets of the character-level language modeling task and the aspect-based sentiment analysis task demonstrate the superiority of the MZU.

scholarly journals Evaluation of Multi-Reanalysis Solar Radiation Products Using Global Surface Observations

Atmosphere ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 42 ◽  
Author(s):  
Xiaomin Peng ◽  
Jiangfeng She ◽  
Shuhua Zhang ◽  
Junzhong Tan ◽  
Yang Li
Keyword(s):  
Solar Radiation ◽  
Large Scale ◽  
Spatial Scales ◽  
Global Solar Radiation ◽  
Hydrological Process ◽  
China Meteorological Administration ◽  
Surface Solar Radiation ◽  
Climate Zones ◽  
Tropical Regions ◽  
Spatial Coverage

Solar radiation incident at the Earth’s surface is an essential driver of the energy exchange between the atmosphere and the surface and is also an important input variable in the research on the surface eco-hydrological process. The reanalysis solar radiation dataset is characterized by a long time series and wide spatial coverage and is used in the research of large-scale eco-hydrological processes. Due to certain errors in their production process of the reanalysis of solar radiation products, reanalysis products should be evaluated before application. In this study, three global solar-radiation reanalysis products (ERA-Interim; JRA-55; and NCEP-DOE) in different temporal scales and climate zones were evaluated using surface solar-radiation observations from the National Meteorological Information Center of the China Meteorological Administration (CMA, Beijing, China) and the Global Energy Balance Archive (GEBA, Zürich, Switzerland) from 2000 to 2009. All reanalysis products (ERA-Interim; JRA-55; and NCEP-DOE) overestimated with an annual bias of 14.86 W/m2, 22.61 W/m2, and 31.85 W/m2; monthly bias of 15.17 W/m2, 21.29 W/m2, and 36.91 W/m2; and seasonal bias of 15.08 W/m2, 21.21 W/m2, and 36.69 W/m2, respectively. In different Köppen climate zones, the annual solar radiation of ERA-Interim performed best in cold regions with a bias of 10.30 W/m2 and absolute relative error (ARE) of 8.98%. However, JRA-55 and NCEP-DOE showed the best performance in tropical regions with a bias of 20.08 W/m2 and −0.12 W/m2, and ARE of 11.00% and 9.68%, respectively. Overall, through the evaluations across different temporal and spatial scales, the rank of the three reanalysis products in order was the ERA-Interim, JRA-55, and NCEP-DOE. In addition, based on the evaluation, we analyzed the relationship between the error (ARE) of the reanalysis products and cloud cover, aerosol, and water vapor, which significantly influences solar radiation and we found that cloud was the main cause for errors in the three solar radiation reanalysis products. The above can provide a reference for the application and downscaling of the three solar radiation reanalysis products.

scholarly journals Identifying and Ranking Potential Driver Genes of Alzheimer's Disease Using Weighted Co-Expression Network Analysis

2021 ◽  
Author(s):  
Liang-Yong Xia ◽  
Lihong Tang ◽  
Hui Huang ◽  
Jie Luo
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Network Analysis ◽  
Drug Targets ◽  
Critical Role ◽  
Driver Genes ◽  
Risk Genes ◽  
Multiple Datasets ◽  
Network Modules ◽  
Go Terms

Abstract Background: Alzheimer's disease (AD) is one of the most common neurodegenerative diseases. Identification of AD-related genes from transcriptomics provided new direction to the mechanism for finding potential targets for drug therapy.Methods: We mined gene co-expression network modules from differentially expressed genes (DEGs) of AD and normal samples in multiple datasets by weighted gene co-expression network analysis (WGCNA). A convergent functional genomic (CFG) method was used to prioritize potential driver genes.Results: The 7567 DEGs were enriched significantly with 61 KEGG pathway and 242 GO terms. Then, the genes in 5 AD-specific modules obtained significantly from DEGs were interconnected with well-known AD risk genes in common PPI network. Remarkably, compared to the number of Tau production-related genes, Aβ play a more critical role. Lastly, the 23 potential driver genes was prioritized by CFG method from 5 AD-specific modules.Conclusions: Identification of AD-related genes could be useful for understanding pathophysiology of AD and looking for candidates drug targets.

scholarly journals An Investigation of the Southern Ocean Surface Temperature Variability Using Long-Term Optimum Interpolation SST Data

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Megha Maheshwari ◽  
Rajkumar Kamaljit Singh ◽  
Sandip Rashmikant Oza ◽  
Raj Kumar
Keyword(s):  
Southern Ocean ◽  
El Niño ◽  
El Nino ◽  
Linear Trend ◽  
Critical Role ◽  
La Niña ◽  
Optimum Interpolation ◽  
La Nina ◽  
Sst Anomaly

An attempt is made to understand the long-term variability of SST using NOAA optimum interpolation SST data for the period (1982–2011) in the Southern Ocean. This dataset has been used (i) to study the interannual variability in SST anomaly and (ii) to carry out regression analysis to compute linear trend in the annual averaged Southern Ocean SST. It is observed that summer season exhibits more variability than winter. Moreover, El Nino/La Nina events apparently play a critical role in the variability of Southern Ocean SST. Thus, higher SST anomalies were observed in El Nino years (e.g., 1983), while cooler anomalies were seen during La Nina years (e.g., 1985). In addition, the eastern and western sides of Antarctica experience episodes of warm and cold SST. Western parts of the Southern Ocean experienced higher anomalies during 1992, 1993, and 1994, while the eastern part experienced positive anomalies in 1997, 1998, 2002, and 2003. The paper also highlights the different regions of the Southern Ocean showing statistically significant positive/negative trends in the variability of interannual average SST. However, in general, the Southern Ocean as a whole is showing a weak interannual cooling trend in SST.

scholarly journals Contrasting controls on Congo Basin evaporation at the two rainfall peaks

2020 ◽  
Author(s):  
David Crowhurst ◽  
Simon Dadson ◽  
Jian Peng ◽  
Richard Washington
Keyword(s):  
Sensible Heat Flux ◽  
Vapour Pressure Deficit ◽  
Lower Surface ◽  
Congo Basin ◽  
Shortwave Radiation ◽  
Net Radiation ◽  
Area Index ◽  
The North ◽  
North Eastern ◽  
Main Component

AbstractEvaporation is a crucial driver of Congo Basin climate, but the dynamics controlling the seasonality of basin evaporation are not well understood. This study aims to discover why evaporation on the basin-wide average is lower at the November rainfall peak than the March rainfall peak, despite similar rainfall. Using 16-year mean LandFlux-EVAL data, we find that evaporation is lower in November than March in the rainforest and the eastern savannah. The ERA5-Land reanalysis, which effectively reproduces this pattern, shows that transpiration is the main component responsible for lower evaporation in these regions. Using ERA5-Land, we find the following contrasting controls on transpiration, and therefore evaporation, at the two rainfall peaks: (a) In the northern rainforest, there is lower leaf area index (LAI) in November, driven by lower surface downward shortwave radiation (DSR), and lower vapour pressure deficit (VPD) in November, driven by lower sensible heat flux that results from lower net radiation. The combination of lower LAI and VPD explains lower transpiration, and therefore lower evaporation, in November. (b) In the southern rainforest, and in the north-eastern savannah, there is lower LAI in November, driven by lower surface DSR, and this explains lower transpiration, and therefore lower evaporation, in November. (c) In the south-eastern savannah, there is lower LAI in November, driven by lower volumetric water content (VWC), and this explains lower transpiration, and therefore lower evaporation, in November. Collectively, these contrasting controls at the two rainfall peaks explain why the basin-wide average evaporation is lower in November than March.

scholarly journals Wetlands Cool Land Surface Temperature in Tropical Regions but Warm in Boreal Regions

2021 ◽  
Vol 13 (8) ◽  
pp. 1439
Author(s):  
Yuxuan Wu ◽  
Yi Xi ◽  
Maoyuan Feng ◽  
Shushi Peng
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Regional Climate ◽  
Critical Role ◽  
Cooling Effect ◽  
Tropical Regions ◽  
Ground Heat Flux ◽  
The Difference ◽  
The Impact

Wetlands play a critical role in global hydrological and biogeochemical cycles. Regulating the regional climate is one of the most important ecosystem services of natural wetlands. However, the impact of wetlands on local temperature on the global scale and the attribution is still unclear. This study utilizes the satellite-based products (land surface temperature (LST), albedo, and evapotranspiration (ET)) to evaluate the difference in LST between wetlands and their adjacent landcover types and the possible drivers. Here we show that on average for the whole year, wetlands have a cooling effect in tropical regions, but have a warming effect in boreal regions. The impacts of wetlands on LST show great seasonality in the boreal regions; i.e., the wetlands have a warming effect in winter but a cooling effect in summer. The difference in albedo and ET between wetlands and the other landcover types only interprets 30% of temporal variation of the difference in LST. Due to the large water storage in wetlands, the ground heat flux (G) may interpret the rest of the impact, absorbing energy in summer and releasing energy in winter in wetlands, which has often been neglected in previous studies. Our results indicate that it is critical to comprehensively consider the effects of wetland restoration in different regions to realize potential climatic benefits in the future.

scholarly journals Influence of multi-decadal meteorological variability on the reference evpotranspirtion in hot and humid coastal town of Annamalainagar in Tamil Nadu state

MAUSAM ◽  
2021 ◽  
Vol 71 (1) ◽  
pp. 45-56
Author(s):  
MURUGAPPAN A ◽  
MANIKUMARI N ◽  
MOHAN S
Keyword(s):  
Tamil Nadu ◽  
Reference Evapotranspiration ◽  
Meteorological Parameter ◽  
Vapour Pressure Deficit ◽  
Weather Data ◽  
Net Radiation ◽  
Sunshine Hours ◽  
Daily Weather Data ◽  
Tamil Nadu State ◽  
Decadal Trend

Reference evapotranspiration (ETo) is a key pointer of atmospheric evaporation demand and has been extensively used to describe the hydrological change. In this study, the reference evapotranspiration over the hot and humid town, Annamalainagar, very near to the east coast in Tamilnadu State, India, have been estimated employing the FAO Penman-Monteith (PM) method and the observed daily weather data during 1977-2016. The objective of the present study is two-fold: (i) To identify the multi-decadal trend of the various measured meteorological parameters namely, mean air temperature (Tmean), vapour pressure deficit (VPD), actual sunshine hours (SSH), net radiation (Rn) and wind speed (WS) at the study location and (ii) To identify the main contributing meteorological parameter for the detected decreasing trend in ETo over the multi-decadal period.

scholarly journals One hundred years of climate change in Mexico

2018 ◽  
Author(s):  
Carolina Ureta ◽  
Ángela Cuervo-Robayo ◽  
Miguel A. Gómez-Albores ◽  
Anny K. Meneses Mosquera ◽  
Oswaldo Téllez Valdés ◽  
...  
Keyword(s):  
Climate Change ◽  
Decision Making ◽  
High Spatial Resolution ◽  
Linear Trend ◽  
Management Strategies ◽  
Tropical Regions ◽  
Rates Of Change ◽  
Biogeographic Provinces ◽  
Linear Trend Analysis ◽  
Quality And Reliability

Spatial assessments of historical climate change are of paramount importance to focus research and conservation efforts. Despite the fact that there are global climatic databases available at high spatial resolution, they present some shortcomings to evaluate historic trends of climate change and their impacts on biodiversity. These databases span over a single period in the late 20th and early 21th centuries and their quality and reliability in many regions is compromise because they have not been produce with all information available for all regions. Therefore, in this contribution we developed climatic surfaces for Mexico for three periods that cover most of the 20th and early 21th centuries: t1-1940 (1910-1949), t2-1970 (1950-1979) and t3-2000 (1980-2009), and characterize climate change rates of the biogeographic provinces of Mexico via a linear trend analysis of monthly values and a Mann-Kendall analysis. Our results indicate that rates of change and trends have not been uniform across Mexico: Nearctic provinces had suffered higher and more consistent trends of change than southern tropical regions. Central and southern provinces cooled down at the beginning of the 20th century, but warmed up consistently since the 1970s. Precipitation has generally increased throughout the country, being more notorious in northern provinces. We aim to provide modellers with a set of climate surfaces that may help decision-making to improve management strategies for biodiversity conservation.

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