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Observations, Modeling, and Impacts of Climate Extremes

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A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (31 December 2019) | Viewed by 47404

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Special Issue Editors

Dr. Jian Peng

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School of Geography and the Environment, University of Oxford, South Parks Road, Oxford OX1 3QY, UK
Interests: remote sensing; water cycle; climate extremes; land–atmosphere interaction; land surface modeling
Special Issues, Collections and Topics in MDPI journals

Dr. Guoyong Leng

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Guest Editor

Environmental Change Institute, University of Oxford South Parks Road, Oxford OX1 3QY, UK
Interests: land surface modeling; climate change; natural hazards; agricultural production; hydrological cycle

Dr. Zheng Duan

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Guest Editor

Chair of Hydrology and River Basin Management, Technical University of Munich, Arcisstrasse 21, 80333 Munich, Germany
Interests: remote sensing; hydrological modeling; evaporation; satellite altimetry; land cover classification

Prof. Dr. Weidong Guo

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Guest Editor

Institute for Climate and Global Change Research, School of Atmospheric Sciences, Nanjing University, No. 163, Xian Lin Road, Nanjing, China
Interests: land surface modeling; land–atmosphere interactions; regional model; downscaling

Special Issue Information

Dear Colleagues,

One of the great global challenges we are facing is climate change. One major concern of climate change is the increase in extreme events, which have been reported by observational studies. Extreme events, such as heavy precipitation, floods, heatwaves, wildfires, and droughts have devastating impacts on many aspects of society and economy. There is a strong need to better understand and identify the mechanisms of extreme events, analyze their impacts, and project future changes. The recent advances in satellite remote sensing and the development of relevant satellite-based climate products provide great potential for hydro-climatic extremes studies. The aim of this Special Issue is to invite contributions that use various approaches, particularly satellite remote sensing and numerical/statistical models, to monitor, simulate, and forecast the spatial-temporal patterns of hydro-climatic extremes, and assess their impacts on society, economy, agriculture, and human health. We would like to invite you to contribute to this Special Issue. Manuscripts are encouraged to cover a wide range of topics, which may include, but are not limited to:

Observations of hydro-climatic extremes
Modeling hydro-climate extremes of the past and future
Assessment of hydro-climatic impacts across sectors
Uncertainties analyses of satellite observations and models
Regional and global climate extremes analyses, e.g., droughts, floods, heat waves, and extreme precipitation
Early warning and forecasting of climate extremes
Managing hydro-climatic extremes

We look forward to your contributions to this exciting Special Issue.

Dr. Jian Peng
Dr. Guoyong Leng
Dr. Zheng Duan
Prof. Dr. Weidong Guo
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Observations
Earth system modeling
Climate change
Extremes
Trend analysis
Uncertainty analysis
Societal impacts

Published Papers (10 papers)

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Research

21 pages, 7537 KiB

Open AccessArticle

Satellite-Based Operational Real-Time Drought Monitoring in the Transboundary Lancang–Mekong River Basin

by Xuejun Zhang, Yanping Qu, Miaomiao Ma, Hui Liu, Zhicheng Su, Juan Lv, Jian Peng, Guoyong Leng, Xiaogang He and Chongli Di

Remote Sens. 2020, 12(3), 376; https://doi.org/10.3390/rs12030376 - 24 Jan 2020

Cited by 11 | Viewed by 4400

Abstract

Existing gauging networks are sparse and not readily available in real-time over the transboundary Lancang–Mekong River (LMR) basin, making it difficult to accurately identify drought. In this study, we aimed to build an operational real-time Lancang–Mekong drought monitor (LMDM), through combining satellite real-time data and the Variable Infiltration Capacity (VIC) hydrological model at a 0.25° spatial resolution. Toward this, three VIC runs were conducted: (1) a 60-year (1951–2010) historical simulation driven by Princeton’s global meteorological forcing (PGF) for yielding ‘normal’ conditions (PGF-VIC), wherein the VIC was calibrated with 20-year observed streamflow at six hydrological stations; (2) a short-period (2011–2014) simulation to bridge the gap between the historical and the real-time modeling; (3) the real-time (2015–present) simulation driven by bias-corrected satellite data, wherein the real-time soil moisture (SM) estimate was expressed as percentile (relative to the ‘normal’) for drought monitoring. Results show that VIC can successfully reproduce the observed hydrographs, with the Nash–Sutcliffe efficiency exceeding 0.70 and the relative bias mostly within 15%. Assessment on the performance of LMDM shows that the real-time SM estimates bear good spatial similarity to the reference, with the correlation coefficient beyond 0.80 across >70% of the domain. In terms of drought monitoring, the LMDM can reasonably reproduce the two recorded droughts, implying extreme droughts covering the Lower LMR during 2004/05 and widespread severe 2009/10 drought across the upper domain. The percentage drought area implied by the LMDM and the reference is close, corresponding to 66% and 60%, 43% and 40%, and 44% and 36% for each typical drought month. Since January 2015, the LMDM was running in an operational mode, from which the 2016 unprecedented drought was successfully identified in Mekong Delta. This study highlights the LMDM’s capability for reliable real-time drought monitoring, which can serve as a valuable drought early warning prototype for other data-poor regions. Full article

(This article belongs to the Special Issue Observations, Modeling, and Impacts of Climate Extremes)

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18 pages, 4163 KiB

Open AccessArticle

Estimation of Land Surface Heat Fluxes Based on Landsat 7 ETM+ Data and Field Measurements over the Northern Tibetan Plateau

by Nan Ge, Lei Zhong, Yaoming Ma, Meilin Cheng, Xian Wang, Mijun Zou and Ziyu Huang

Remote Sens. 2019, 11(24), 2899; https://doi.org/10.3390/rs11242899 - 05 Dec 2019

Cited by 11 | Viewed by 4539

Abstract

Land surface heat fluxes consist of the net radiation flux, soil heat flux, sensible heat flux, and latent heat flux. The estimation of these fluxes is essential to the study of energy transfer in land–atmosphere systems. In this paper, Landsat 7 ETM+ SLC-on data were applied to estimate the land surface heat fluxes on the northern Tibetan Plateau using the SEBS (surface energy balance system) model, in combination with the calculation of field measurements at CAMP/Tibet (Coordinated Enhanced Observing Period (CEOP) Asia–Australia Monsoon Project on the Tibetan Plateau) automatic weather stations based on the combinatory method (CM) for comparison. The root mean square errors between the satellite estimations and the CM calculations for the net radiation flux, soil heat flux, sensible heat flux, and latent heat flux were 49.2 W/m², 46.3 W/m², 68.2 W/m², and 54.9 W/m², respectively. The results reveal that land surface heat fluxes all present significant seasonal variability. Apart from the sensible heat flux, the satellite-estimated net radiation flux, soil heat flux, and latent heat flux exhibited a trend of summer > spring > autumn > winter. In summer, spring, autumn, and winter, respectively, the median values of the net radiation flux (631.8 W/m², 583.0 W/m², 404.4 W/m², 314.3 W/m²), soil heat flux (40.9 W/m², 37.9 W/m², 26.1 W/m², 20.5 W/m²), sensible heat flux (252.7 W/m², 219.5 W/m², 221.4 W/m², 204.8 W/m²), and latent heat flux (320.1 W/m², 298.3 W/m², 142.3 W/m², 75.5 W/m²) exhibited distinct seasonal diversity. From November to April, the in situ sensible heat flux is higher than the latent heat flux; the opposite is true between June and September, leaving May and October as transitional months. For water bodies, alpine meadows and other main underlying surface types, sensible and latent heat flux generally present contrasting and complementary spatial distributions. Due to the 15–60 m resolution of the Landsat 7 ETM+ data, the distribution of land surface heat fluxes can be used as an indicator of complex underlying surface types over the northern Tibetan Plateau. Full article

(This article belongs to the Special Issue Observations, Modeling, and Impacts of Climate Extremes)

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18 pages, 2776 KiB

Open AccessArticle

Copula-Based Abrupt Variations Detection in the Relationship of Seasonal Vegetation-Climate in the Jing River Basin, China

by Jing Zhao, Shengzhi Huang, Qiang Huang, Hao Wang, Guoyong Leng, Jian Peng and Haixia Dong

Remote Sens. 2019, 11(13), 1628; https://doi.org/10.3390/rs11131628 - 09 Jul 2019

Cited by 40 | Viewed by 3965

Abstract

Understanding the changing relationships between vegetation coverage and precipitation/temperature (P/T) and then exploring their potential drivers are highly necessary for ecosystem management under the backdrop of a changing environment. The Jing River Basin (JRB), a typical eco-environmentally vulnerable region of the Loess Plateau, was chosen to identify abrupt variations of the relationships between seasonal Normalized Difference Vegetation Index (NDVI) and P/T through a copula-based method. By considering the climatic/large-scale atmospheric circulation patterns and human activities, the potential causes of the non-stationarity of the relationship between NDVI and P/T were revealed. Results indicated that (1) the copula-based framework introduced in this study is more reasonable and reliable than the traditional double-mass curves method in detecting change points of vegetation and climate relationships; (2) generally, no significant change points were identified during 1982–2010 at the 95% confidence level, implying the overall stationary relationship still exists, while the relationships between spring NDVI and P/T, autumn NDVI and P have slightly changed; (3) teleconnection factors (including Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO), Niño 3.4, and sunspots) have a more significant influence on the relationship between seasonal NDVI and P/T than local climatic factors (including potential evapotranspiration and soil moisture); (4) negative human activities (expansion of farmland and urban areas) and positive human activities (“Grain For Green” program) were also potential factors affecting the relationship between NDVI and P/T. This study provides a new and reliable insight into detecting the non-stationarity of the relationship between NDVI and P/T, which will be beneficial for further revealing the connection between the atmosphere and ecosystems. Full article

(This article belongs to the Special Issue Observations, Modeling, and Impacts of Climate Extremes)

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21 pages, 5180 KiB

Open AccessArticle

Spatiotemporal Variation of Drought and Associated Multi-Scale Response to Climate Change over the Yarlung Zangbo River Basin of Qinghai–Tibet Plateau, China

by Hao Li, Liu Liu, Baoying Shan, Zhicheng Xu, Qiankun Niu, Lei Cheng, Xingcai Liu and Zongxue Xu

Remote Sens. 2019, 11(13), 1596; https://doi.org/10.3390/rs11131596 - 04 Jul 2019

Cited by 33 | Viewed by 4507 | Correction

Abstract

Drought is one of the most widespread and threatening natural disasters in the world, which has terrible impacts on agricultural irrigation and production, ecological environment, and socioeconomic development. As a critical ecologically fragile area located in southwest China, the Yarlung Zangbo River (YZR) basin is sensitive and vulnerable to climate change and human activities. Hence, this study focused on the YZR basin and attempted to investigate the spatiotemporal variations of drought and associated multi-scale response to climate change based on the scPDSI (self-calibrating Palmer drought severity index) and CRU (climate research unit) data. Results showed that: (1) The YZR basin has experienced an overall wetting process from 1956 to 2015, while a distinct transition period in the mid 1990s (from wet to dry) was detected by multiple statistical methods. (2) Considering the spatial variation of the scPDSI, areas showing the significantly wetting process with increasing scPDSI values were mostly located in the arid upstream and midstream regions, which accounted for over 48% area of the YZR basin, while areas exhibiting the drying tendency with decreasing scPDSI values were mainly concentrated in the humid southern part of the YZR basin, dominating the transition period from wet to dry, to which more attention should be paid. (3) By using the EEMD (ensemble empirical mode decomposition) method, the scPDSI over the YZR basin showed quasi-3-year and quasi-9-year cycles at the inter-annual scale, while quasi-15-year and quasi-56-year cycles were detected at the inter-decadal scale. The reconstructed inter-annual scale showed a better capability to represent the abrupt change characteristic of drought, which was also more influential to the original time series with a variance contribution of 55.3%, while the inter-decadal scale could be used to portray the long-term drought variation process with a relative lower variance contribution of 29.1%. (4) The multi-scale response of drought to climate change indicated that changes of precipitation (PRE) and diurnal temperature range (DTR) were the major driving factors in the drought variation at different time scales. Compared with potential evapotranspiration (PET), DTR was a much more important climate factor associated with drought variations by altering the energy balance, which is more obvious over the YZR basin distributed with extensive snow cover and glaciers. These findings could provide important implications for ecological environment protection and sustainable socioeconomic development in the YZR basin and other high mountain regions. Full article

(This article belongs to the Special Issue Observations, Modeling, and Impacts of Climate Extremes)

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18 pages, 3749 KiB

Open AccessArticle

A Study on the Assessment of Multi-Source Satellite Soil Moisture Products and Reanalysis Data for the Tibetan Plateau

by Meilin Cheng, Lei Zhong, Yaoming Ma, Mijun Zou, Nan Ge, Xian Wang and Yuanyuan Hu

Remote Sens. 2019, 11(10), 1196; https://doi.org/10.3390/rs11101196 - 20 May 2019

Cited by 51 | Viewed by 4387

Abstract

Soil moisture is a key variable in the process of land–atmosphere energy and water exchange. Currently, there are a large number of operational satellite-derived soil moisture products and reanalysis soil moisture products available. However, due to the lack of in situ soil moisture measurements over the Tibetan Plateau (TP), their accuracy and applicability are unclear. Based on the in situ measurements of the soil moisture observing networks established at Maqu, Naqu, Ali, and Shiquanhe (Sq) by the Institute of Tibetan Plateau Research, the Chinese Academy of Sciences, the Northwest Institute of Eco-Environmental Resources, the Chinese Academy of Sciences and the University of Twente over the TP, the accuracy and reliability of the European Space Agency Climate Change Initiative Soil Moisture version 4.4 (ESA CCI SM v4.4) soil moisture products and the European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) soil moisture product were evaluated. The spatiotemporal distributions and interannual variations of the soil moisture were analyzed. Further, the climatological soil moisture changing trends across the TP were explored. The results show that with regard to the whole plateau, the combined product performs the best (unbiased root-mean-square error (ubRMSE) = 0.043 m³/m³, R = 0.66), followed by the active product (ubRMSE = 0.048 m³/m³, R = 0.62), the passive product (ubRMSE = 0.06 m³/m³, R = 0.61), and the ERA5 soil moisture product (ubRMSE = 0.067 m³/m³, R = 0.52). Considering the good spatiotemporal data continuity of the ERA5 soil moisture product, the ERA5 soil moisture data from 1979 to 2018 were used to analyze the climatological soil moisture changing trend for the entire TP surface. It was found that there was an increasing trend of soil moisture across the TP, which was consistent with the overall trends of increasing precipitation and decreasing evaporation. Moreover, the shrinkage of the cryosphere in conjunction with the background TP warming presumably contribute to soil moisture change. Full article

(This article belongs to the Special Issue Observations, Modeling, and Impacts of Climate Extremes)

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17 pages, 7977 KiB

Open AccessArticle

Widespread Decline in Vegetation Photosynthesis in Southeast Asia Due to the Prolonged Drought During the 2015/2016 El Niño

by Xin Qian, Bo Qiu and Yongguang Zhang

Remote Sens. 2019, 11(8), 910; https://doi.org/10.3390/rs11080910 - 14 Apr 2019

Cited by 24 | Viewed by 5016

Abstract

El Niño events are known to be associated with climate extremes and have substantial impacts on the global carbon cycle. The drought induced by strong El Niño event occurred in the tropics during 2015 and 2016. However, it is still unclear to what extent the drought could affect photosynthetic activities of crop and forest in Southeast Asia. Here, we used the satellite solar-induced chlorophyll fluorescence (SIF), which is a proxy of actual photosynthesis, along with traditional vegetation indices (Enhanced Vegetation Index, EVI) and total water storage to investigate the impacts of El Niño–induced droughts on vegetation productivity of the forest and crop in the Southeast Asia. We found that SIF was more sensitive to the water stress than traditional vegetation indices (EVI) to monitor drought for both evergreen broadleaf forest and croplands in Southeast Asia. The higher solar radiation partly offset the negative effects of droughts on the vegetation productivity, leading to a larger decrease of SIF yield (SIF_yield) than SIF. Therefore, SIF_yield had a larger reduction and was more sensitive to precipitation deficit than SIF during the drought. The comparisons of retrieved column-average dry-air mole fraction of atmospheric carbon dioxide with SIF demonstrated the reduction of CO₂ uptake by vegetation in Southeast Asia during the drought. This study highlights that SIF is more beneficial than EVI to be an indicator to characterize and monitor the dynamics of drought in tropical vegetated regions. Full article

(This article belongs to the Special Issue Observations, Modeling, and Impacts of Climate Extremes)

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25 pages, 5121 KiB

Open AccessArticle

Comparing Multiple Precipitation Products against In-Situ Observations over Different Climate Regions of Pakistan

by Waheed Ullah, Guojie Wang, Gohar Ali, Daniel Fiifi Tawia Hagan, Asher Samuel Bhatti and Dan Lou

Remote Sens. 2019, 11(6), 628; https://doi.org/10.3390/rs11060628 - 14 Mar 2019

Cited by 64 | Viewed by 4859

Abstract

Various state-of-the-art gridded satellite precipitation products (GPPs) have been derived from remote sensing and reanalysis data and are widely used in hydrological studies. An assessment of these GPPs against in-situ observations is necessary to determine their respective strengths and uncertainties. GPPs developed from satellite observations as a primary source were compared to in-situ observations, namely the Climate Hazard group Infrared Precipitation with Stations (CHIRPS), Multi-Source Weighted-Ensemble Precipitation (MSWEP), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) and Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis (TMPA). These products were compared to in-situ data from 51 stations, spanning 1998–2016, across Pakistan on daily, monthly, annual and interannual time scales. Spatiotemporal climatology was well captured by all products, with more precipitation in the north eastern parts during the monsoon months and vice-versa. Daily precipitation with amount larger than 10 mm showed significant (95%, Kolmogorov-Smirnov test) agreement with the in-situ data, especially TMPA, followed by CHIRPS and MSWEP. At monthly scales, there were significant correlations (R) between the GPPs and in-situ records, suggesting similar dynamics; however, statistical metrics suggested that the performance of these products varies from north towards south. Temporal agreement on an interannual scale was higher in the central and southern parts which followed precipitation seasonality. TMPA performed the best, followed in order by CHIRPS, MSWEP and PERSIANN-CDR. Full article

(This article belongs to the Special Issue Observations, Modeling, and Impacts of Climate Extremes)

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12 pages, 6680 KiB

Open AccessArticle

A Set of Satellite-Based Near Real-Time Meteorological Drought Monitoring Data over China

by Xuejun Zhang, Zhicheng Su, Juan Lv, Weiwei Liu, Miaomiao Ma, Jian Peng and Guoyong Leng

Remote Sens. 2019, 11(4), 453; https://doi.org/10.3390/rs11040453 - 22 Feb 2019

Cited by 10 | Viewed by 4350

Abstract

A high-resolution and near real-time drought monitoring dataset has not been made readily available in drought-prone China, except for the low-resolution global product. Here we developed a set of near real-time meteorological drought data at a 0.25° spatial resolution over China, by seamlessly merging the satellite-based near real-time (RT) precipitation (3B42RTv7) into the high-quality gauge-based retrospective product (CN05.1) using the quantile-mapping (QM) bias-adjustment method. Comparing the standard precipitation index (SPI) from the satellite-gauge merged product (SGMP) with that from the retrospective ground product CN05.1 (OBS) shows that the SGMP reproduces well the observed spatial distribution of SPI and the pattern of meteorological drought across China, at both the 6-month and 12-month time scales. In contrast, the UN-SGMP generated by merging the unadjusted raw satellite precipitation into the gauging data shows systematical overestimation of the SPI, leaving less meteorological droughts to be identified. Furthermore, the SGMP is found to be able to capture the inter-annual variation of percentage area in meteorological droughts. These validation results suggest that the newly developed drought dataset is reliable for monitoring meteorological drought dynamics in near real-time. This dataset will be routinely updated as the satellite RT precipitation is made available, thus facilitating near real-time drought diagnosis in China. Full article

(This article belongs to the Special Issue Observations, Modeling, and Impacts of Climate Extremes)

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17 pages, 4924 KiB

Open AccessArticle

Comparison of the Vegetation Effect on ET Partitioning Based on Eddy Covariance Method at Five Different Sites of Northern China

by Hongchang Hu, Lajiao Chen, Hui Liu, Mohd Yawar Ali Khan, Qiang Tie, Xuejun Zhang and Fuqiang Tian

Remote Sens. 2018, 10(11), 1755; https://doi.org/10.3390/rs10111755 - 07 Nov 2018

Cited by 24 | Viewed by 3502

Abstract

Vegetation exerts profound influences on evapotranspiration (ET) partitioning. Many studies have demonstrated the positive impact of vegetation cover on the ratio of transpiration (T) to ET. Whether it is universally true with regard to different vegetation types and different sites is understudied. In this study, five sites in Northern China with different vegetation types were selected for comparison study.ET partitioning is conducted using an approach based on the concept of the underlying water use efficiency with eddy covariance measurements. The results show various patterns of vegetation’s effects over ET partitioning and, when compared with existing studies, also reveal a new relationship between the T/ET ratio and Normalized Difference Vegetation Index (NDVI) at some of the sites. At the alpine meadow site, the T/ET ratio gradually increase when NDVI is low and rapidly increase as NDVI go beyond a certain value, whereas at the arid shrub site, the T/ET ratio rapidly increase when NDVI is low and plateaus at a certain value when NDVI reaches a relatively high value. In deciduous forest, the T/ET ratio becomes unresponsive to NDVI beyond a threshold value. This study also reveals that irrigation schemes play a major role in determining the correlation between the T/ET ratio and NDVI because the T/ET ratio becomes well correlated with NDVI in case of flood irrigation and irrelevant to NDVI in the case of mulch drip irrigation. Furthermore, this study helps us to understand ET partitioning under different sites and different human activities such as irrigation. These findings can help policymakers to better understand the connection between vegetation and climate change or human activities and provide significant information for water management policy. Full article

(This article belongs to the Special Issue Observations, Modeling, and Impacts of Climate Extremes)

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22 pages, 3882 KiB

Open AccessArticle

GRACE-Based Terrestrial Water Storage in Northwest China: Changes and Causes

by Yangyang Xie, Shengzhi Huang, Saiyan Liu, Guoyong Leng, Jian Peng, Qiang Huang and Pei Li

Remote Sens. 2018, 10(7), 1163; https://doi.org/10.3390/rs10071163 - 23 Jul 2018

Cited by 36 | Viewed by 6872

Abstract

Monitoring variations in terrestrial water storage (TWS) is of great significance for the management of water resources. However, it remains a challenge to continuously monitor TWS variations using in situ observations and hydrological models because of a limited number of gauge stations and the complicated spatial distribution characteristics of TWS. In contrast, the Gravity Recovery and Climate Experiment (GRACE) could overcome the aforementioned restrictions, providing a new reliable means of observing TWS variation. Thus, GRACE was employed to investigate TWS variations in Northwest China (NWC) between April 2002 and March 2016. Unlike previous studies, we focused on the interactions of multiple climatic and vegetational factors, and their combined effects on TWS variation. In addition, we also analyzed the relationship between TWS variations and socioeconomic water consumption. The results indicated that (i) TWS had obvious seasonal variations in NWC, and showed significant decreasing trends in most parts of NWC at the 95% confidence level; (ii) decreasing sunshine duration and wind speed resulted in an increase in TWS in Qinghai province, whereas the increasing air temperature, ameliorative vegetational coverage, and excessive groundwater withdrawal jointly led to a decrease in TWS in the other provinces of NWC; (iii) TWS variations in NWC had a good correlation with water storage variations in cascade reservoirs of the upper Yellow River; and (iv) the overall interactions between multiple climatic and vegetational factors were obvious, and the strong effects of some climatic and vegetational factors could mask the weak influences of other factors in TWS variations in NWC. Hence, it is necessary to focus on the interactions of multiple factors and their combined effects on TWS variations when exploring the causes of TWS variations. Full article

(This article belongs to the Special Issue Observations, Modeling, and Impacts of Climate Extremes)

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