Verbessertes Downscaling meteorologischer Daten für die hydrologische Modellierung in den Tropen unter den Bedingungen des klimatischen Wandels

Parallel to the development of computing science, the understanding of the climate system behaviours and the climate model accuracy and resolution have been considerable improved. It, however, has still not been sufficient for the request of hydrologic modeling at a local scale, especially when focusing on the impacts of climate change. Therefore, it is necessary to carry out a study for a small basin like the Thi Vai basin (approximately 500 km2) in southern Vietnam to provide further information on local changes in climate and to quantify its impacts on hydrological characteristics for present and future periods. Within this study, the technology of statistical downscaling is improved and directly coupled with the outputs of a regional climate model, which contains dynamical downscaling techniques. The regional climate model is implemented with the three self-nesting steps to transfer the information of global climate models into local climate information. The techniques of Model Output Statistics and Two-Step Model are applied and developed to correct the daily temperature and precipitation at the finest resolution of 10 x 10 km, respectively. To quantify the possible impacts of climate change on hydrological characteristics, the water balance model PANTA RHEI is driven by the model output of the dynamic-statistical downscaling. A strategy for future analyses of the reverse effects of changes in the water balance on the outputs of downscaling models is also provided. The main results indicate that: (i) the dynamical climate model overestimates both total precipitation and wet day frequency, although both precipitation and temperature is simulated quite well on the highest horizontal grid resolution that can be reached using a hydrostatic climate model, (ii) the combination of statistical and dynamical downscaling is an effective approach for daily precipitation and temperature series analysis, (iii) a clear climate change signal for temperature and precipitation is found for the Thi Vai basin, (iv) the simulations of the PANTA RHEI model fit well to the observational data, although PANTA RHEI has never been applied in Vietnam before and (v) the changes in meteorological components significantly contribute to potential changes in stream flow in the Thi Vai basin, even if these changes are negligibleZeitgleich zur Entwicklung der Computerwissenschaften verbesserten sich das Verständnis des Verhaltens des Klimasystems und die Genauigkeit und Auflösung der Klimamodelle deutlich. Deshalb ist es notwendig, eine Studie für ein kleines Einzugsgebiet wie das Thi Vai Einzugsgebiet (ca. 500 km2) im südlichen Vietnam durchzuführen, um weitergehende Informationen zu lokalen Klimaveränderungen zu liefern und deren Auswirkungen auf hydrologische Charakteristiken für heutige und zukünftige Zeiträume zu quantifizieren. In dieser Studie wird das statistische Downscaling verbessert und direkt mit dem Output eines regionalen Klimamodells gekoppelt, welches mit einem dynamischen Downscaling produziert wurde. Hier für wird das regionale dynamische Klimamodell zunächst mit 3 Nesting-Schritten angewandt, um die Information von globalen Klimamodellen in lokale Klimainformationen zu übertragen. Die Ergebnisse aus dem letzlen Nesting-Schritt, bei dem ein Gittesnetz von 10 x 10 km angesetzt wurde, werden statistisch wie folgt verbessert: Die MOS (Model Output Statistics)-Technik wurde angewendet, um die tägliche Temperatur zu korrigieren. Die tägliche Niederschlagsmenge wurde durch die TSM (Two-Step Model)-Technik korrigiert. Um die möglichen Auswirkungen des Klimawandels auf hydrologische Charakteristika zu quantifizieren, wird das Wasserhaushaltsmodell PANTA RGHEI mit dem Output des dynamisch-statistischen Downscaling angetrieben. Zusätzlich wird eine strategie für zukünftige Analysen der Rückkopplungseffekte eines veränderten Wasserhaushalts auf den Output von Downscaling-Modellen erarbeitet. Die wichtigsten Ergebnisse zeigen, dass: (i) das dynamische Klimamodell sowohl die Niederschlagsmenge als auch die Anzahl an Regentagen überschätzt, obwohl Niederschlag und Temperatur in der höchstmöglichen horizontalen Auflösung eines hydrostatischen Modells gut simuliert werden, (ii) die Komination von statistischem und dynamischem Downscaling ein effektiver Ansatz für die Analyse von Tagesmittelwerten für Niederschlags- und Temperaturzeitreihen ist, (iii) ein deutliches Klimawandelsignal für Niederschlag und Temperatur identifiziert wurde, (iv) die Simulationen des PANTA RHEI-Modells die Beobachtungsdaten gut widerspiegeln, obwohl PANTA RHEI zuvor nicht für Vietnam angewandt wurde, (v) die Veränderungen der meteorologischen Komponenten deutlich zu den potentiellen Veränderungen des Abflusses in Thi Vai Einzugsgebiet beitragen, auch wenn diese Veränderungen nur geringfügig sin

Assimilation of SMAP products for improving streamflow simulations over tropical climate region — is spatial information more important than temporal information?

Streamflow is one of the key variables in the hydrological cycle. Simulation and forecasting of streamflow are challenging tasks for hydrologists, especially in sparsely gauged areas. Coarse spatial resolution remote sensing soil moisture products (equal to or larger than 9 km) are often assimilated into hydrological models to improve streamflow simulation in large catchments. This study uses the Ensemble Kalman Filter (EnKF) technique to assimilate SMAP soil moisture products at the coarse spatial resolution of 9 km (SMAP 9 km), and downscaled SMAP soil moisture product at the higher spatial resolution of 1 km (SMAP 1 km), into the Soil and Water Assessment Tool (SWAT) to investigate the usefulness of different spatial and temporal resolutions of remotely sensed soil moisture products in streamflow simulation and forecasting. The experiment was set up for eight catchments across the tropical climate of Vietnam, with varying catchment areas from 267 to 6430 km2 during the period 2017–2019. We comprehensively evaluated the EnKF-based SWAT model in simulating streamflow at low, average, and high flow. Our results indicated that high-spatial resolution of downscaled SMAP 1 km is more beneficial in the data assimilation framework in aiding the accuracy of streamflow simulation, as compared to that of SMAP 9 km, especially for the small catchments. Our analysis on the impact of observation resolution also indicates that the improvement in the streamflow simulation with data assimilation is more significant at catchments where downscaled SMAP 1 km has fewer missing observations. This study is helpful for adding more understanding of performances of soil moisture data assimilation based hydrological modelling over the tropical climate region, and exhibits the potential use of remote sensing data assimilation in hydrology

Global component analysis of errors in three satellite-only global precipitation estimates

Revealing the error components of satellite-only precipitation products (SPPs) can help algorithm developers and end-users understand their error features and improve retrieval algorithms. Here, two error decomposition schemes are employed to explore the error components of the IMERG-Late, GSMaP-MVK, and PERSIANN-CCS SPPs over different seasons, rainfall intensities, and topography classes. Global maps of the total bias (total mean squared error) and its three (two) independent components are depicted for the first time. The evaluation results for similar regions are discussed, and it is found that the evaluation results for one region cannot be extended to another similar region. Hit and/or false biases are the major components of the total bias in most overland regions globally. The systematic error contributes less than 20 % of the total error in most areas. Large systematic errors are primarily due to missed precipitation. It is found that the SPPs show different topographic patterns in terms of systematic and random errors. Notably, among the SPPs, GSMaP-MVK shows the strongest topographic dependency of the four bias scores. A novel metric, namely the normalized error component (NEC), is proposed as a means to isolate the impact of topography on the systematic and random errors. Potential methods of improving satellite precipitation retrievals and error adjustment models are discussed.</p

Remote Sensing of Precipitation: Volume 2

Precipitation is a well-recognized pillar in global water and energy balances. An accurate and timely understanding of its characteristics at the global, regional, and local scales is indispensable for a clearer understanding of the mechanisms underlying the Earth’s atmosphere–ocean complex system. Precipitation is one of the elements that is documented to be greatly affected by climate change. In its various forms, precipitation comprises a primary source of freshwater, which is vital for the sustainability of almost all human activities. Its socio-economic significance is fundamental in managing this natural resource effectively, in applications ranging from irrigation to industrial and household usage. Remote sensing of precipitation is pursued through a broad spectrum of continuously enriched and upgraded instrumentation, embracing sensors which can be ground-based (e.g., weather radars), satellite-borne (e.g., passive or active space-borne sensors), underwater (e.g., hydrophones), aerial, or ship-borne

A Review of Earth Observation-Based Drought Studies in Southeast Asia

Drought is a recurring natural climatic hazard event over terrestrial land; it poses devastating threats to human health, the economy, and the environment. Given the increasing climate crisis, it is likely that extreme drought phenomena will become more frequent, and their impacts will probably be more devastating. Drought observations from space, therefore, play a key role in dissimilating timely and accurate information to support early warning drought management and mitigation planning, particularly in sparse in-situ data regions. In this paper, we reviewed drought-related studies based on Earth observation (EO) products in Southeast Asia between 2000 and 2021. The results of this review indicated that drought publications in the region are on the increase, with a majority (70%) of the studies being undertaken in Vietnam, Thailand, Malaysia and Indonesia. These countries also accounted for nearly 97% of the economic losses due to drought extremes. Vegetation indices from multispectral optical remote sensing sensors remained a primary source of data for drought monitoring in the region. Many studies (~21%) did not provide accuracy assessment on drought mapping products, while precipitation was the main data source for validation. We observed a positive association between spatial extent and spatial resolution, suggesting that nearly 81% of the articles focused on the local and national scales. Although there was an increase in drought research interest in the region, challenges remain regarding large-area and long time-series drought measurements, the combined drought approach, machine learning-based drought prediction, and the integration of multi-sensor remote sensing products (e.g., Landsat and Sentinel-2). Satellite EO data could be a substantial part of the future efforts that are necessary for mitigating drought-related challenges, ensuring food security, establishing a more sustainable economy, and the preservation of the natural environment in the region

Proceedings Of The 18th Annual Meeting Of The Asia Oceania Geosciences Society (Aogs 2021)

The 18th Annual Meeting of the Asia Oceania Geosciences Society (AOGS 2021) was held from 1st to 6th August 2021. This proceedings volume includes selected extended abstracts from a challenging array of presentations at this conference. The AOGS Annual Meeting is a leading venue for professional interaction among researchers and practitioners, covering diverse disciplines of geosciences

Hydroclimate variability in central Vietnam: past and present

Central Vietnam is one of only few locations within the Asian Monsoon realm, where the rainy season is associated with the Northeast Winter Monsoon. The winter monsoon in this region is characterised by strong north-easterly winds bringing moisture from the Pacific, leading to intensive rainfall during autumn and winter. This is often associated with natural hazards such as flooding and landslides, threatening the livelihood of millions in this region. Compared with the Asian Summer Monsoon, our knowledge of past and present rainfall variability related to the Northeast Winter Monsoon is more limited, which affects our ability to understand future climate scenarios in this region. This work uses stable isotopes in rainwater and the chemical composition of a stalagmite from central Vietnam to understand the climate in Southeast Asia in the present and past. Cave monitoring and climate simulations indicate that the seasonal cycle in rainwater stable isotopes from central Vietnam does not follow peak rainfall amount, but rather reflects the seasonal shift between the Indian Ocean, providing moisture during summer, and the Pacific Ocean which provides moisture during the rest of the year. This seasonal signal in rainfall oxygen isotopes is partly preserved in cave waters but low values are biased towards the season of recharge in autumn. This work presents the first high-resolution speleothem multi-proxy record from central Vietnam covering the Holocene. By using carbon isotopes and trace elements the history of the Northeast Winter Monsoon was reconstructed. In Southeast Asia, summer and winter monsoons evolved in-phase for most of the Holocene, between 8000 to 3000 years BP (before present). This in-phase relation shifts at 3000 years BP, after which the winter monsoon gets progressively wetter and the summer monsoon progressively drier. Here it is proposed that shifts in the Pacific Walker Circulation controlled the in-phase relation of the monsoons in Southeast Asia until 3000 years BP. Afterwards the summer monsoon was mainly controlled by changes in the Indian Walker Circulation and the winter monsoon by changes in Pacific sea surface temperatures. Investigating central Vietnam’s climate on a seasonal scale during a cool phase between 1600 and 1300 years BP showed that the timing of the ITCZ migration is key in modulating rainfall variability. A cooling of primarily autumn/winter sea surface temperatures in the western Pacific led to a delay of the ITCZ withdrawal during this season, causing enhanced rainfall in central Vietnam. The findings of this work have far-reaching implications for future palaeoclimate studies, such as the interpretation of proxies and the understanding of the monsoonal system in Southeast Asia over the Holocene

Comparison and Bias Correction of TMPA Precipitation Products over the Lower Part of Red–Thai Binh River Basin of Vietnam

As the limitation of rainfall collection by ground measurement has been widely recognized, satellite-based rainfall estimate is a promising high-resolution alternative in both time and space. This study is aimed at exploring the capacity of the satellite-based rainfall product Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), including 3B42V7 research data and its real-time 3B42RT data, by comparing them against data from 29 ground observation stations over the lower part of the Red–Thai Binh River Basin from March 2000 to December 2016. Various statistical metrics were applied to evaluate the TMPA products. The results showed that both 3B42V7 and 3B42RT had weak relationships with daily observations, but 3B42V7 data had strong agreement on the monthly scale compared to 3B42RT. Seasonal analysis showed that 3B42V7 and 3B42RT underestimated rainfall during the dry season and overestimated rainfall during the wet season, with high bias observed for 3B42RT. In addition, detection metrics demonstrated that TMPA products could detect rainfall events in the wet season much better than in the dry season. When rainfall intensity was analyzed, both 3B42V7 and 3B42RT overestimated the no rainfall event during the dry season but underestimated these events during the wet season. Finally, based on the moderate correlation between climatology–topography characteristics and correction factors of linear-scaling (LS) approach, a set of multiple linear models was developed to reduce the error between TMPA products and the observations. The results showed that climatology–topography-based linear-scaling approach (CTLS) significantly reduced the percentage bias (PBIAS) score and moderately improved the Nash–Sutcliffe efficiency (NSE) score. The finding of this paper gives an overview of the capacity of TMPA products in the lower part of the Red–Thai Binh River Basin regarding water resource applications and provides a simple bias correction that can be used to improve the correctness of TMPA products