Articles | Volume 16, issue 5
https://doi.org/10.5194/hess-16-1349-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/hess-16-1349-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
10 May 2012
Research article |
| 10 May 2012
Spatial horizontal correlation characteristics in the land data assimilation of soil moisture
X. Han
Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, Gansu, 730000, China
Forschungszentrum Jülich, Agrosphere (IBG 3), Leo-Brandt-Strasse, 52425 Jülich, Germany
X. Li
Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, Gansu, 730000, China
H. J. Hendricks Franssen
Forschungszentrum Jülich, Agrosphere (IBG 3), Leo-Brandt-Strasse, 52425 Jülich, Germany
H. Vereecken
Forschungszentrum Jülich, Agrosphere (IBG 3), Leo-Brandt-Strasse, 52425 Jülich, Germany
C. Montzka
Forschungszentrum Jülich, Agrosphere (IBG 3), Leo-Brandt-Strasse, 52425 Jülich, Germany
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Theory development
Variation and attribution of probable maximum precipitation of China using a high-resolution dataset in a changing climate
Drought cascades across multiple systems in Central Asia identified based on the dynamic space–time motion approach
What is the Priestley–Taylor wet-surface evaporation parameter? Testing four hypotheses
Understanding the diurnal cycle of land–atmosphere interactions from flux site observations
Breakdown in precipitation–temperature scaling over India predominantly explained by cloud-driven cooling
Historical droughts manifest an abrupt shift to a wetter Tibetan Plateau
Citizen rain gauges improve hourly radar rainfall bias correction using a two-step Kalman filter
Dynamical forcings in heavy precipitation events over Italy: lessons from the HyMeX SOP1 campaign
Water vapor isotopes indicating rapid shift among multiple moisture sources for the 2018–2019 winter extreme precipitation events in southeastern China
Spatiotemporal and cross-scale interactions in hydroclimate variability: a case-study in France
Relative humidity gradients as a key constraint on terrestrial water and energy fluxes
A climatological benchmark for operational radar rainfall bias reduction
The precipitation variability of the wet and dry season at the interannual and interdecadal scales over eastern China (1901–2016): the impacts of the Pacific Ocean
Flash drought onset over the contiguous United States: sensitivity of inventories and trends to quantitative definitions
A skewed perspective of the Indian rainfall–El Niño–Southern Oscillation (ENSO) relationship
Imprints of evaporative conditions and vegetation type in diurnal temperature variations
A universal Standardized Precipitation Index candidate distribution function for observations and simulations
A review of the complementary principle of evaporation: from the original linear relationship to generalized nonlinear functions
Model representation of the coupling between evapotranspiration and soil water content at different depths
Combined impacts of ENSO and MJO on the 2015 growing season drought on the Canadian Prairies
Exploring the relationships between warm-season precipitation, potential evaporation, and “apparent” potential evaporation at site scale
Future extreme precipitation intensities based on a historic event
Interannual-to-multidecadal hydroclimate variability and its sectoral impacts in northeastern Argentina
Impact of ENSO regimes on developing- and decaying-phase precipitation during rainy season in China
Variations in the correlation between teleconnections and Taiwan's streamflow
A gain–loss framework based on ensemble flow forecasts to switch the urban drainage–wastewater system management towards energy optimization during dry periods
The residence time of water in the atmosphere revisited
A systematic assessment of drought termination in the United Kingdom
From meteorological to hydrological drought using standardised indicators
Impact of two different types of El Niño events on runoff over the conterminous United States
Flood sensitivity of the Bavarian Alpine Foreland since the late Middle Ages in the context of internal and external climate forcing factors
Novel indices for the comparison of precipitation extremes and floods: an example from the Czech territory
Multi-annual droughts in the English Lowlands: a review of their characteristics and climate drivers in the winter half-year
Fractional snow-covered area parameterization over complex topography
Comment on "Technical Note: On the Matt–Shuttleworth approach to estimate crop water requirements" by Lhomme et al. (2014)
A review of droughts on the African continent: a geospatial and long-term perspective
Synchronicity of historical dry spells in the Southern Hemisphere
Continental moisture recycling as a Poisson process
Linking ENSO and heavy rainfall events over coastal British Columbia through a weather pattern classification
Impact of elevation and weather patterns on the isotopic composition of precipitation in a tropical montane rainforest
A new perspective on the spatio-temporal variability of soil moisture: temporal dynamics versus time-invariant contributions
Understanding hydroclimate processes in the Murray-Darling Basin for natural resources management
An analytical model for soil-atmosphere feedback
On the factors influencing surface-layer energy closure and their seasonal variability over the semi-arid Loess Plateau of Northwest China
Spatial moments of catchment rainfall: rainfall spatial organisation, basin morphology, and flood response
Scaling and trends of hourly precipitation extremes in two different climate zones – Hong Kong and the Netherlands
The response of Iberian rivers to the North Atlantic Oscillation
Copula-based downscaling of spatial rainfall: a proof of concept
Towards understanding hydroclimatic change in Victoria, Australia – preliminary insights into the "Big Dry"
Extracting statistical parameters of extreme precipitation from a NWP model
Jinghua Xiong, Shenglian Guo, Abhishek, Jiabo Yin, Chongyu Xu, Jun Wang, and Jing Guo
Hydrol. Earth Syst. Sci., 28, 1873–1895, https://doi.org/10.5194/hess-28-1873-2024, https://doi.org/10.5194/hess-28-1873-2024, 2024
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Temporal variability and spatial heterogeneity of climate systems challenge accurate estimation of probable maximum precipitation (PMP) in China. We use high-resolution precipitation data and climate models to explore the variability, trends, and shifts of PMP under climate change. Validated with multi-source estimations, our observations and simulations show significant spatiotemporal divergence of PMP over the country, which is projected to amplify in future due to land–atmosphere coupling.
Lu Tian, Markus Disse, and Jingshui Huang
Hydrol. Earth Syst. Sci., 27, 4115–4133, https://doi.org/10.5194/hess-27-4115-2023, https://doi.org/10.5194/hess-27-4115-2023, 2023
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Anthropogenic global warming accelerates the drought evolution in the water cycle, increasing the unpredictability of drought. The evolution of drought is stealthy and challenging to track. This study proposes a new framework to capture the high-precision spatiotemporal progression of drought events in their evolutionary processes and characterize their feature further. It is crucial for addressing the systemic risks within the hydrological cycle associated with drought mitigation.
Richard D. Crago, Jozsef Szilagyi, and Russell J. Qualls
Hydrol. Earth Syst. Sci., 27, 3205–3220, https://doi.org/10.5194/hess-27-3205-2023, https://doi.org/10.5194/hess-27-3205-2023, 2023
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The Priestley–Taylor equation is widely used in hydrologic, climate, and meteorological models to estimate evaporation. α represents the impact of dry air that is carried into the region; this occurs even in extensive saturated regions. Four hypotheses regarding the nature of α are evaluated. Data from 171 FLUXNET stations were used to test the hypotheses. The best-supported hypothesis sees α as a constant fraction of the distance between theoretical minimum and maximum values.
Eunkyo Seo and Paul A. Dirmeyer
Hydrol. Earth Syst. Sci., 26, 5411–5429, https://doi.org/10.5194/hess-26-5411-2022, https://doi.org/10.5194/hess-26-5411-2022, 2022
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This study presents the climatology of the observed land–atmosphere interactions on a subdaily timescale during the warm season from flux site observations. Multivariate metrics are employed to examine the land, atmosphere, and combined couplings, and a mixing diagram is adopted to understand the coevolution of the moist and thermal energy budget within the atmospheric mixed layer. The diurnal cycles of both mixing diagrams and hourly land–atmosphere couplings exhibit hysteresis.
Sarosh Alam Ghausi, Subimal Ghosh, and Axel Kleidon
Hydrol. Earth Syst. Sci., 26, 4431–4446, https://doi.org/10.5194/hess-26-4431-2022, https://doi.org/10.5194/hess-26-4431-2022, 2022
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The observed response of extreme precipitation to global warming remains unclear with significant regional variations. We show that a large part of this uncertainty can be removed when the imprint of clouds in surface temperatures is removed. We used a thermodynamic systems approach to remove the cloud radiative effect from temperatures. We then found that precipitation extremes intensified with global warming at positive rates which is consistent with physical arguments and model simulations.
Yongwei Liu, Yuanbo Liu, Wen Wang, Han Zhou, and Lide Tian
Hydrol. Earth Syst. Sci., 26, 3825–3845, https://doi.org/10.5194/hess-26-3825-2022, https://doi.org/10.5194/hess-26-3825-2022, 2022
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This study investigated the wetting and drying of the Tibetan Plateau (TP) from variations in soil moisture (SM) droughts. We found the TP experienced an abrupt and significant wetting shift in the middle to late 1990s, not merely the steady trends given in literature. This shift is dominated by precipitation and attributed to the North Atlantic Oscillation. The wetting shift indicates a climate regime change. Our innovative work provides implications for further knowledge of the TP climate.
Punpim Puttaraksa Mapiam, Monton Methaprayun, Thom Bogaard, Gerrit Schoups, and Marie-Claire Ten Veldhuis
Hydrol. Earth Syst. Sci., 26, 775–794, https://doi.org/10.5194/hess-26-775-2022, https://doi.org/10.5194/hess-26-775-2022, 2022
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The density of rain gauge networks plays an important role in radar rainfall bias correction. In this work, we aimed to assess the extent to which daily rainfall observations from a dense network of citizen scientists improve the accuracy of hourly radar rainfall estimates in the Tubma Basin, Thailand. Results show that citizen rain gauges significantly enhance the performance of radar rainfall bias adjustment up to a range of about 40 km from the center of the citizen rain gauge network.
Mario Marcello Miglietta and Silvio Davolio
Hydrol. Earth Syst. Sci., 26, 627–646, https://doi.org/10.5194/hess-26-627-2022, https://doi.org/10.5194/hess-26-627-2022, 2022
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The main results emerging from the HyMeX SOP1 campaign and in the subsequent research activity in three Italian target areas are highlighted through conceptual models and through the identification of the relevant mesoscale environmental characteristics conducive to heavy rain events.
Tao Xu, Hongxi Pang, Zhaojun Zhan, Wangbin Zhang, Huiwen Guo, Shuangye Wu, and Shugui Hou
Hydrol. Earth Syst. Sci., 26, 117–127, https://doi.org/10.5194/hess-26-117-2022, https://doi.org/10.5194/hess-26-117-2022, 2022
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In this study, we presented stable isotopes in atmospheric water vapor and precipitation for five extreme winter precipitation events in Nanjing, southeastern China, from December 2018 to February 2019. Our results imply that multiple moisture sources and the rapid shift among them are important conditions for sustaining extreme precipitation events, especially in the relatively cold and dry winter.
Manuel Fossa, Bastien Dieppois, Nicolas Massei, Matthieu Fournier, Benoit Laignel, and Jean-Philippe Vidal
Hydrol. Earth Syst. Sci., 25, 5683–5702, https://doi.org/10.5194/hess-25-5683-2021, https://doi.org/10.5194/hess-25-5683-2021, 2021
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Hydro-climate observations (such as precipitation, temperature, and river discharge time series) reveal very complex behavior inherited from complex interactions among the physical processes that drive hydro-climate viability. This study shows how even small perturbations of a physical process can have large consequences on some others. Those interactions vary spatially, thus showing the importance of both temporal and spatial dimensions in better understanding hydro-climate variability.
Yeonuk Kim, Monica Garcia, Laura Morillas, Ulrich Weber, T. Andrew Black, and Mark S. Johnson
Hydrol. Earth Syst. Sci., 25, 5175–5191, https://doi.org/10.5194/hess-25-5175-2021, https://doi.org/10.5194/hess-25-5175-2021, 2021
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Here, we present a novel physically based evaporation model to demonstrate that vertical relative humidity (RH) gradients from the land surface to the atmosphere tend to evolve towards zero due to land–atmosphere equilibration processes. Collapsing RH gradients on daily to yearly timescales indicate an emergent land–atmosphere equilibrium, making it possible to determine evapotranspiration using only meteorological information, independent of land surface conditions and vegetation controls.
Ruben Imhoff, Claudia Brauer, Klaas-Jan van Heeringen, Hidde Leijnse, Aart Overeem, Albrecht Weerts, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 25, 4061–4080, https://doi.org/10.5194/hess-25-4061-2021, https://doi.org/10.5194/hess-25-4061-2021, 2021
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Significant biases in real-time radar rainfall products limit the use for hydrometeorological forecasting. We introduce CARROTS (Climatology-based Adjustments for Radar Rainfall in an OperaTional Setting), a set of fixed bias reduction factors to correct radar rainfall products and to benchmark other correction algorithms. When tested for 12 Dutch basins, estimated rainfall and simulated discharges with CARROTS generally outperform those using the operational mean field bias adjustments.
Tao Gao, Fuqiang Cao, Li Dan, Ming Li, Xiang Gong, and Junjie Zhan
Hydrol. Earth Syst. Sci., 25, 1467–1481, https://doi.org/10.5194/hess-25-1467-2021, https://doi.org/10.5194/hess-25-1467-2021, 2021
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The rainfall in eastern China is principally concentrated from April–September. Changes are roughly coincident with phase shifts of the El Niño–Southern Oscillation (ENSO) in both the dry (October–March) and wet (April–September) seasons, and the Pacific Decadal Oscillation (PDO) triggers a stronger effect on precipitation in the wet season. The interannual and interdecadal rainfall variability over eastern China is substantially modulated by drivers originating from the Pacific Ocean.
Mahmoud Osman, Benjamin F. Zaitchik, Hamada S. Badr, Jordan I. Christian, Tsegaye Tadesse, Jason A. Otkin, and Martha C. Anderson
Hydrol. Earth Syst. Sci., 25, 565–581, https://doi.org/10.5194/hess-25-565-2021, https://doi.org/10.5194/hess-25-565-2021, 2021
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Our study of flash droughts' definitions over the United States shows that published definitions yield markedly different inventories of flash drought geography and frequency. Results suggest there are several pathways that can lead to events that are characterized as flash droughts. Lack of consensus across definitions helps to explain apparent contradictions in the literature on trends and indicates the selection of a definition is important for accurate monitoring of different mechanisms.
Justin Schulte, Frederick Policielli, and Benjamin Zaitchik
Hydrol. Earth Syst. Sci., 24, 5473–5489, https://doi.org/10.5194/hess-24-5473-2020, https://doi.org/10.5194/hess-24-5473-2020, 2020
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Wavelet coherence is now a commonly used method for detecting scale-dependent relationships between time series. In this study, the concept of wavelet coherence is generalized to higher-order wavelet coherence methods that quantify the relationship between higher-order statistical moments associated with two time series. The methods are applied to the El Niño–Southern Oscillation (ENSO) and the Indian monsoon to show that the ENSO–Indian monsoon relationship is impacted by ENSO nonlinearity.
Annu Panwar, Maik Renner, and Axel Kleidon
Hydrol. Earth Syst. Sci., 24, 4923–4942, https://doi.org/10.5194/hess-24-4923-2020, https://doi.org/10.5194/hess-24-4923-2020, 2020
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Here we examine the effect of evaporative cooling across different vegetation types. Evaporation cools surface temperature significantly in short vegetation. In the forest, the high aerodynamic conductance explains 56 % of the reduced surface temperature. Therefore, the main cooling agent in the forest is the high aerodynamic conductance and not evaporation. Additionally, we propose the diurnal variation in surface temperature as being a potential indicator of evaporation in short vegetation.
Patrick Pieper, André Düsterhus, and Johanna Baehr
Hydrol. Earth Syst. Sci., 24, 4541–4565, https://doi.org/10.5194/hess-24-4541-2020, https://doi.org/10.5194/hess-24-4541-2020, 2020
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The Standardized Precipitation Index (SPI) is a widely accepted drought index. SPI normalizes the precipitation distribution via a probability density function (PDF). However, which PDF properly normalizes SPI is still disputed. We suggest using a previously mostly overlooked PDF, namely the exponentiated Weibull distribution. The proposed PDF ensures the normality of the index. We demonstrate this – for the first time – for all common accumulation periods in both observations and simulations.
Songjun Han and Fuqiang Tian
Hydrol. Earth Syst. Sci., 24, 2269–2285, https://doi.org/10.5194/hess-24-2269-2020, https://doi.org/10.5194/hess-24-2269-2020, 2020
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The complementary principle is an important methodology for estimating actual evaporation by using routinely observed meteorological variables. This review summaries its 56-year development, focusing on how related studies have shifted from adopting a symmetric linear complementary relationship to employing generalized nonlinear functions. We also compare the polynomial and sigmoid types of generalized complementary functions and discuss their future development.
Jianxiu Qiu, Wade T. Crow, Jianzhi Dong, and Grey S. Nearing
Hydrol. Earth Syst. Sci., 24, 581–594, https://doi.org/10.5194/hess-24-581-2020, https://doi.org/10.5194/hess-24-581-2020, 2020
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Accurately estimating coupling of evapotranspiration (ET) and soil water content (θ) at different depths is key to investigating land–atmosphere interaction. Here we examine whether the model can accurately represent surface θ (θs) versus ET coupling and vertically integrated θ (θv) versus ET coupling. We find that all models agree with observations that θs contains slightly more information with fPET than θv. In addition, an ET scheme is crucial for accurately estimating coupling of θ and ET.
Zhenhua Li, Yanping Li, Barrie Bonsal, Alan H. Manson, and Lucia Scaff
Hydrol. Earth Syst. Sci., 22, 5057–5067, https://doi.org/10.5194/hess-22-5057-2018, https://doi.org/10.5194/hess-22-5057-2018, 2018
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The research started by investigating the 2015 growing season drought over the Canadian Prairies and evolved into investigating the connection between growing season rain deficit in the Prairies and MJO (20–90 days tropical oscillation in convective storms). With warm central Pacific sea surface temperature, strong MJOs in the western Pacific cause Rossby wave trains that propagate downstream and favour upper-level ridges and rain deficits over the Canadian Prairies during the growing season.
Xi Chen and Steven G. Buchberger
Hydrol. Earth Syst. Sci., 22, 4535–4545, https://doi.org/10.5194/hess-22-4535-2018, https://doi.org/10.5194/hess-22-4535-2018, 2018
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Based on warm season data from 259 weather stations across the US, we analyze the correlation between precipitation, potential evaporation, and “apparent” potential evaporation (measured by pan evaporation). Over 93 % of the stations show negative correlation between precipitation and
apparentpotential evaporation, but no clear relationship is shown between precipitation and potential evaporation. The collected data points follow the trend of the newly derived Bouchet–Budyko curve.
Iris Manola, Bart van den Hurk, Hans De Moel, and Jeroen C. J. H. Aerts
Hydrol. Earth Syst. Sci., 22, 3777–3788, https://doi.org/10.5194/hess-22-3777-2018, https://doi.org/10.5194/hess-22-3777-2018, 2018
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In a warmer climate, it is expected that precipitation intensities will increase and form a considerable risk of high-impact precipitation extremes. We investigate how observed extreme precipitation events would look like if they took place in a future warmer climate. This study applies three methods to transform a historic extreme precipitation event in the Netherlands to a similar event in a future warmer climate, thus compiling a
future weatherscenario.
Miguel A. Lovino, Omar V. Müller, Gabriela V. Müller, Leandro C. Sgroi, and Walter E. Baethgen
Hydrol. Earth Syst. Sci., 22, 3155–3174, https://doi.org/10.5194/hess-22-3155-2018, https://doi.org/10.5194/hess-22-3155-2018, 2018
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This study examines hydroclimate variability in northeastern Argentina; advances the understanding of its links with global SST forcing; and discusses its impacts on water resources, agriculture and human settlements. Interannual-to-multidecadal variability led to frequent extreme events. Severe floods affected agriculture, livestock productivity, and forced population displacements. Droughts affected water resources, causing water and food scarcity. Increased temperatures reduced crop yields.
Qing Cao, Zhenchun Hao, Feifei Yuan, Zhenkuan Su, Ronny Berndtsson, Jie Hao, and Tsring Nyima
Hydrol. Earth Syst. Sci., 21, 5415–5426, https://doi.org/10.5194/hess-21-5415-2017, https://doi.org/10.5194/hess-21-5415-2017, 2017
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This study analyzed the rainy-season precipitation in China influenced by various ENSO types. The precipitation anomalies were investigated under different ENSO types, which may be attributed to the combined influence of anti-cyclone in the western North Pacific and the Indian monsoon. The results improve the understanding of linkages between the precipitation and global teleconnection patterns. The results suggest a certain predictability of flood and drought related to different ENSO types.
Chia-Jeng Chen and Tsung-Yu Lee
Hydrol. Earth Syst. Sci., 21, 3463–3481, https://doi.org/10.5194/hess-21-3463-2017, https://doi.org/10.5194/hess-21-3463-2017, 2017
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Regional hydro-climatic variables are modulated by large-scale, reoccurring climate oscillations. In this article, the authors provide both statistical and physical evidence of how Taiwan’s summertime streamflow is strongly correlated with specific teleconnection patterns dominating cyclonic activity in the western North Pacific. However, such correlation can be strengthened or weakened by notable climate regime shifts, illustrating the pitfall of empirical seasonal forecasting.
Vianney Courdent, Morten Grum, Thomas Munk-Nielsen, and Peter S. Mikkelsen
Hydrol. Earth Syst. Sci., 21, 2531–2544, https://doi.org/10.5194/hess-21-2531-2017, https://doi.org/10.5194/hess-21-2531-2017, 2017
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Urban drainage and wastewater systems are heavily impacted by precipitation. Hence, weather forecasts are valuable in improving their management. However, forecasts are intrinsically uncertain, especially when fine model resolution is required, which is the case for urban hydrology. Handling uncertainty is challenging for decision makers. This study presents an economic framework to support the decision-making process by providing information on when acting on the forecast is beneficial.
Ruud J. van der Ent and Obbe A. Tuinenburg
Hydrol. Earth Syst. Sci., 21, 779–790, https://doi.org/10.5194/hess-21-779-2017, https://doi.org/10.5194/hess-21-779-2017, 2017
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This research seeks out to answer a fundamental question about the functioning of the water cycle in the atmosphere: how much time does a water particle spend in the atmosphere? Based on state-of-the-art data, we derive a global average residence time of water in the atmosphere of 8–10 days. We further show in this paper how the residence time of water varies in time and space. This serves to illustrate why it is so difficult to make weather predictions on timescales longer than a week.
Simon Parry, Robert L. Wilby, Christel Prudhomme, and Paul J. Wood
Hydrol. Earth Syst. Sci., 20, 4265–4281, https://doi.org/10.5194/hess-20-4265-2016, https://doi.org/10.5194/hess-20-4265-2016, 2016
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This paper identifies periods of recovery from drought in 52 river flow records from the UK between 1883 and 2013. The approach detects 459 events that vary in space and time. This large dataset allows individual events to be compared with others in the historical record. The ability to objectively appraise contemporary events against the historical record has not previously been possible, and may allow water managers to prepare for a range of outcomes at the end of a drought.
Lucy J. Barker, Jamie Hannaford, Andrew Chiverton, and Cecilia Svensson
Hydrol. Earth Syst. Sci., 20, 2483–2505, https://doi.org/10.5194/hess-20-2483-2016, https://doi.org/10.5194/hess-20-2483-2016, 2016
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Standardised meteorological indicators are widely used in drought monitoring, but applications to hydrological drought are less extensive. Here we assess the utility of standardised indicators for characterising drought duration, severity and propagation in a diverse set of 121 UK catchments. Spatial variations in streamflow drought characteristics reflect differences in drought propagation behaviour that are themselves largely driven by heterogeneity in catchment properties around the UK.
T. Tang, W. Li, and G. Sun
Hydrol. Earth Syst. Sci., 20, 27–37, https://doi.org/10.5194/hess-20-27-2016, https://doi.org/10.5194/hess-20-27-2016, 2016
O. Böhm, J. Jacobeit, R. Glaser, and K.-F. Wetzel
Hydrol. Earth Syst. Sci., 19, 4721–4734, https://doi.org/10.5194/hess-19-4721-2015, https://doi.org/10.5194/hess-19-4721-2015, 2015
M. Müller, M. Kašpar, A. Valeriánová, L. Crhová, E. Holtanová, and B. Gvoždíková
Hydrol. Earth Syst. Sci., 19, 4641–4652, https://doi.org/10.5194/hess-19-4641-2015, https://doi.org/10.5194/hess-19-4641-2015, 2015
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Three proposed indices combine return periods of precipitation totals or discharges with the size of the affected area. Precipitation indices also determine actual duration of either extreme or seasonally abnormal precipitation events. A unified design of the indices enables one to easily compare inter-annual and seasonal distributions of events, which is demonstrated by 50 maximum events in the Czech Republic during the period 1961-2010, including the June 2013 floods.
C. K. Folland, J. Hannaford, J. P. Bloomfield, M. Kendon, C. Svensson, B. P. Marchant, J. Prior, and E. Wallace
Hydrol. Earth Syst. Sci., 19, 2353–2375, https://doi.org/10.5194/hess-19-2353-2015, https://doi.org/10.5194/hess-19-2353-2015, 2015
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The English Lowlands is a heavily populated, water-stressed region, which is vulnerable to long droughts typically associated with dry winters. We conduct a long-term (1910-present) quantitative analysis of precipitation, flow and groundwater droughts for the region, and then review potential climatic drivers. No single driver is dominant, but we demonstrate a physical link between La Nina conditions, winter rainfall and long droughts in the region.
N. Helbig, A. van Herwijnen, J. Magnusson, and T. Jonas
Hydrol. Earth Syst. Sci., 19, 1339–1351, https://doi.org/10.5194/hess-19-1339-2015, https://doi.org/10.5194/hess-19-1339-2015, 2015
W. J. Shuttleworth
Hydrol. Earth Syst. Sci., 18, 4403–4406, https://doi.org/10.5194/hess-18-4403-2014, https://doi.org/10.5194/hess-18-4403-2014, 2014
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This paper explains the Matt-Shuttleworth approach clearly, simply and concisely. It shows how this approach can be implemented using a few simple equations and provides access to ancillary calculation resources that can be used for such implementation. If the crop water requirement community considered it preferable to use the Penman-Monteith equation to estimate crop water requirements directly for all crops, this could now be done using the Matt-Shuttleworth approach.
I. Masih, S. Maskey, F. E. F. Mussá, and P. Trambauer
Hydrol. Earth Syst. Sci., 18, 3635–3649, https://doi.org/10.5194/hess-18-3635-2014, https://doi.org/10.5194/hess-18-3635-2014, 2014
D. C. Verdon-Kidd and A. S. Kiem
Hydrol. Earth Syst. Sci., 18, 2257–2264, https://doi.org/10.5194/hess-18-2257-2014, https://doi.org/10.5194/hess-18-2257-2014, 2014
H. F. Goessling and C. H. Reick
Hydrol. Earth Syst. Sci., 17, 4133–4142, https://doi.org/10.5194/hess-17-4133-2013, https://doi.org/10.5194/hess-17-4133-2013, 2013
P. Brigode, Z. Mićović, P. Bernardara, E. Paquet, F. Garavaglia, J. Gailhard, and P. Ribstein
Hydrol. Earth Syst. Sci., 17, 1455–1473, https://doi.org/10.5194/hess-17-1455-2013, https://doi.org/10.5194/hess-17-1455-2013, 2013
D. Windhorst, T. Waltz, E. Timbe, H.-G. Frede, and L. Breuer
Hydrol. Earth Syst. Sci., 17, 409–419, https://doi.org/10.5194/hess-17-409-2013, https://doi.org/10.5194/hess-17-409-2013, 2013
H. Mittelbach and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 16, 2169–2179, https://doi.org/10.5194/hess-16-2169-2012, https://doi.org/10.5194/hess-16-2169-2012, 2012
A. J. E. Gallant, A. S. Kiem, D. C. Verdon-Kidd, R. C. Stone, and D. J. Karoly
Hydrol. Earth Syst. Sci., 16, 2049–2068, https://doi.org/10.5194/hess-16-2049-2012, https://doi.org/10.5194/hess-16-2049-2012, 2012
B. Schaefli, R. J. van der Ent, R. Woods, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 16, 1863–1878, https://doi.org/10.5194/hess-16-1863-2012, https://doi.org/10.5194/hess-16-1863-2012, 2012
X. Xiao, H. C. Zuo, Q. D. Yang, S. J. Wang, L. J. Wang, J. W. Chen, B. L. Chen, and B. D. Zhang
Hydrol. Earth Syst. Sci., 16, 893–910, https://doi.org/10.5194/hess-16-893-2012, https://doi.org/10.5194/hess-16-893-2012, 2012
D. Zoccatelli, M. Borga, A. Viglione, G. B. Chirico, and G. Blöschl
Hydrol. Earth Syst. Sci., 15, 3767–3783, https://doi.org/10.5194/hess-15-3767-2011, https://doi.org/10.5194/hess-15-3767-2011, 2011
G. Lenderink, H. Y. Mok, T. C. Lee, and G. J. van Oldenborgh
Hydrol. Earth Syst. Sci., 15, 3033–3041, https://doi.org/10.5194/hess-15-3033-2011, https://doi.org/10.5194/hess-15-3033-2011, 2011
J. Lorenzo-Lacruz, S. M. Vicente-Serrano, J. I. López-Moreno, J. C. González-Hidalgo, and E. Morán-Tejeda
Hydrol. Earth Syst. Sci., 15, 2581–2597, https://doi.org/10.5194/hess-15-2581-2011, https://doi.org/10.5194/hess-15-2581-2011, 2011
M. J. van den Berg, S. Vandenberghe, B. De Baets, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 15, 1445–1457, https://doi.org/10.5194/hess-15-1445-2011, https://doi.org/10.5194/hess-15-1445-2011, 2011
A. S. Kiem and D. C. Verdon-Kidd
Hydrol. Earth Syst. Sci., 14, 433–445, https://doi.org/10.5194/hess-14-433-2010, https://doi.org/10.5194/hess-14-433-2010, 2010
J. Eliasson, O. Rögnvaldsson, and T. Jonsson
Hydrol. Earth Syst. Sci., 13, 2233–2240, https://doi.org/10.5194/hess-13-2233-2009, https://doi.org/10.5194/hess-13-2233-2009, 2009
Cited articles
Anderson, J. L.: An ensemble adjustment Kalman filter for data assimilation, Mon. Weather Rev., 129, 2884–2903, 2001.
Anterrieu, E.: On the Detection and Quantification of RFI in L1a Signals Provided by SMOS, IEEE T. Geosci. Remote, 49, 3986–3992, https://doi.org/10.1109/Tgrs.2011.2136350, 2011.
Bishop, C. H., Etherton, B. J., and Majumdar, S. J.: Adaptive sampling with the ensemble transform Kalman filter, Part I: Theoretical aspects, Mon. Weather Rev., 129, 420–436, 2001.
Bonan, G. B., Levis, S., Kergoat, L., and Oleson, K. W.: Landscapes as patches of plant functional types: An integrating concept for climate and ecosystem models, Global Biogeochem. Cy., 16, 1021, https://doi.org/10.1029/2000gb001360, 2002.
Brocca, L., Melone, F., Moramarco, T., and Morbidelli, R.: Spatial-temporal variability of soil moisture and its estimation across scales, Water Resour. Res., 46, W02516, https://doi.org/10.1029/2009wr008016, 2010a.
Brocca, L., Melone, F., Moramarco, T., Wagner, W., Naeimi, V., Bartalis, Z., and Hasenauer, S.: Improving runoff prediction through the assimilation of the ASCAT soil moisture product, Hydrol. Earth Syst. Sci., 14, 1881–1893, https://doi.org/10.5194/hess-14-1881-2010, 2010b.
Burgers, G., van Leeuwen, P. J., and Evensen, G.: Analysis scheme in the ensemble Kalman filter, Mon. Weather Rev., 126, 1719–1724, 1998.
Chiles, J. P. and Delfiner, P.: Geostatistics: modeling spatial uncertainty, Wiley-Interscience, 1999.
Coll, C., Wan, Z. M., and Galve, J. M.: Temperature-based and radiance-based validations of the V5 MODIS land surface temperature product, J. Geophys. Res.-Atmos., 114, D20102, https://doi.org/10.1029/2009jd012038, 2009.
Dai, Y. J., Zeng, X. B., Dickinson, R. E., Baker, I., Bonan, G. B., Bosilovich, M. G., Denning, A. S., Dirmeyer, P. A., Houser, P. R., Niu, G. Y., Oleson, K. W., Schlosser, C. A., and Yang, Z. L.: The Common Land Model, B. Am. Meteorol. Soc., 84, 1013–1023, https://doi.org/10.1175/Bams-84-8-1013, 2003.
De Lannoy, G. J. M., Verhoest, N. E. C., Houser, P. R., Gish, T. J., and Van Meirvenne, M.: Spatial and temporal characteristics of soil moisture in an intensively monitored agricultural field (OPE(3)), J. Hydrol., 331, 719–730, 2006.
De Lannoy, G. J. M., Houser, P. R., Verhoest, N. E. C., and Pauwels, V. R. N.: Adaptive Soil Moisture Profile Filtering for Horizontal Information Propagation in the Independent Column-Based CLM2.0, J. Hydrometeorol., 10, 766–779, https://doi.org/10.1175/2008jhm1037.1, 2009.
Dharssi, I., Bovis, K. J., Macpherson, B., and Jones, C. P.: Operational assimilation of ASCAT surface soil wetness at the Met Office, Hydrol. Earth Syst. Sci., 15, 2729–2746, https://doi.org/10.5194/hess-15-2729-2011, 2011.
Dorigo, W. A., Scipal, K., Parinussa, R. M., Liu, Y. Y., Wagner, W., de Jeu, R. A. M., and Naeimi, V.: Error characterisation of global active and passive microwave soil moisture datasets, Hydrol. Earth Syst. Sci., 14, 2605–2616, https://doi.org/10.5194/hess-14-2605-2010, 2010.
Drusch, M., Scipal, K., de Rosnay, P., Balsamo, G., Andersson, E., Bougeault, P., and Viterbo, P.: Towards a Kalman Filter based soil moisture analysis system for the operational ECMWF Integrated Forecast System, Geophys. Res. Lett., 36, L10401, L10401, https://doi.org/10.1029/2009gl037716, 2009.
Dunne, S. and Entekhabi, D.: An ensemble-based reanalysis approach to land data assimilation, Water Resour. Res., 41, W02013, https://doi.org/10.1029/2004wr003449, 2005.
Entekhabi, D., Njoku, E. G., O'Neill, P. E., Kellogg, K. H., Crow, W. T., Edelstein, W. N., Entin, J. K., Goodman, S. D., Jackson, T. J., Johnson, J., Kimball, J., Piepmeier, J. R., Koster, R. D., Martin, N., McDonald, K. C., Moghaddam, M., Moran, S., Reichle, R., Shi, J. C., Spencer, M. W., Thurman, S. W., Tsang, L., and Van Zyl, J.: The Soil Moisture Active Passive (SMAP) Mission, Proc. IEEE, 98, 704–716, 2010.
FAO, Iiasa,: Harmonized World Soil Database (version 1.1), FAO, Rome, Italy and IIASA, Laxenburg, Austria, 2010.
Flores, A. N., Ivanov, V. Y., Entekhabi, D., and Bras, R. L.: Impact of Hillslope-Scale Organization of Topography, Soil Moisture, Soil Temperature, and Vegetation on Modeling Surface Microwave Radiation Emission, IEEE T. Geosci. Remote, 47, 2557–2571, https://doi.org/10.1109/Tgrs.2009.2014743, 2009.
Ghent, D., Kaduk, J., Remedios, J., Ardo, J., and Balzter, H.: Assimilation of land surface temperature into the land surface model JULES with an ensemble Kalman filter, J. Geophys. Res.-Atmos., 115, D19112, https://doi.org/10.1029/2010jd014392, 2010.
Goovaerts, P.: Geostatistics for natural resources evaluation, Oxford University Press, USA, 1997.
Greybush, S. J., Kalnay, E., Miyoshi, T., Ide, K., and Hunt, B. R.: Balance and Ensemble Kalman Filter Localization Techniques, Mon. Weather Rev., 139, 511–522, https://doi.org/10.1175/2010MWR3328.1, 2010.
Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., and Jarvis, A.: Very high resolution interpolated climate surfaces for global land areas, Int. J. Climatol., 25, 1965–1978, https://doi.org/10.1002/Joc.1276, 2005.
Houtekamer, P. L. and Mitchell, H. L.: Data assimilation using an ensemble Kalman filter technique, Mon. Weather Rev., 126, 796–811, https://doi.org/10.1175/1520-0493(1998)126<0796:DAUAEK>2.0.CO;2, 1998.
Hunt, B. R., Kostelich, E. J., and Szunyogh, I.: Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter, Physica D, 230, 112–126, https://doi.org/10.1016/j.physd.2006.11.008, 2007.
Jarvis, A., Reuter, H. I., Nelson, A., and Guevara, E.: Hole-filled seamless SRTM data V4, International Centre for Tropical Agriculture, available from: http://srtm.csi.cgiar.org (last access: May 2012), 2008.
Kalnay, E., Li, H., Miyoshi, T., Yang, S. C., and Ballabrera-Poy, J.: 4-D-Var or ensemble Kalman filter?, Tellus A, 59, 758–773, https://doi.org/10.1111/j.1600-0870.2007.00261.x, 2007.
Kerr, Y. H., Waldteufel, P., Wigneron, J. P., Delwart, S., Cabot, F., Boutin, J., Escorihuela, M. J., Font, J., Reul, N., Gruhier, C., and Others: The SMOS Mission: New Tool for Monitoring Key Elements ofthe Global Water Cycle, Proc. IEEE, 98, 666–687, 2010.
Kumar, S. V., Reichle, R. H., Koster, R. D., Crow, W. T., and Peters-Lidard, C. D.: Role of Subsurface Physics in the Assimilation of Surface Soil Moisture Observations, J. Hydrometeorol., 10, 1534–1547, https://doi.org/10.1175/2009jhm1134.1, 2009.
Lakhankar, T., Jones, A. S., Combs, C. L., Sengupta, M., Haar, T. H. V., and Khanbilvardi, R.: Analysis of Large Scale Spatial Variability of Soil Moisture Using a Geostatistical Method, Sensors, 10, 913–932, https://doi.org/10.3390/S100100913, 2010.
Lawrence, P. J. and Chase, T. N.: Representing a new MODIS consistent land surface in the Community Land Model (CLM 3.0), J. Geophys. Res.-Biogeo., 112, G01023, https://doi.org/10.1029/2006jg000168, 2007.
Li, F. Q., Crow, W. T., and Kustas, W. P.: Towards the estimation root-zone soil moisture via the simultaneous assimilation of thermal and microwave soil moisture retrievals, Adv. Water Resour., 33, 201–214, https://doi.org/10.1016/j.advwatres.2009.11.007, 2010.
Li, X., Huang, C. L., Che, T., Jin, R., Wang, S. G., Wang, J. M., Gao, F., Zhang, S. W., Qiu, C. J., and Wang, C. H.: Development of a Chinese land data assimilation system: its progress and prospects, Prog. Nat. Sci., 17, 881–892, 2007.
Li, X., Li, X. W., Li, Z. Y., Ma, M. G., Wang, J., Xiao, Q., Liu, Q., Che, T., Chen, E. X., Yan, G. J., Hu, Z. Y., Zhang, L. X., Chu, R. Z., Su, P. X., Liu, Q. H., Liu, S. M., Wang, J. D., Niu, Z., Chen, Y., Jin, R., Wang, W. Z., Ran, Y. H., Xin, X. Z., and Ren, H. Z.: Watershed Allied Telemetry Experimental Research, J. Geophys. Res.-Atmos., 114, D22103, https://doi.org/10.1029/2008jd011590, 2009.
Liston, G. E. and Elder, K.: A meteorological distribution system for high-resolution terrestrial modeling (MicroMet), J. Hydrometeorol., 7, 217–234, 2006.
Liu, Q., Reichle, R. H., Bindlish, R., Cosh, M. H., Crow, W. T., de Jeu, R., De Lannoy, G. J. M., Huffman, G. J., and Jackson, T. J.: The Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System, J. Hydrometeorol., 12, 750–765, https://doi.org/10.1175/Jhm-D-10-05000.1, 2011.
Mahfouf, J. F.: Assimilation of satellite-derived soil moisture from ASCAT in a limited-area NWP model, Q. J. Roy. Meteorol. Soc., 136, 784–798, https://doi.org/10.1002/Qj.602, 2010.
Matzler, C. and Standley, A.: Relief effects for passive microwave remote sensing, Int. J. Remote Sens., 21, 2403–2412, 2000.
Minasny, B. and McBratney, A. B.: The Matern function as a general model for soil variograms, Geoderma, 128, 192–207, https://doi.org/10.1016/j.geoderma.2005.04.003, 2005.
Miyoshi, T. and Yamane, S.: Local ensemble transform Kalman filtering with an AGCM at a T159/L48 resolution, Mon. Weather Rev., 135, 3841–3861, https://doi.org/10.1175/2007mwr1873.1, 2007.
Montzka, C., Moradkhani, H., Weihermuller, L., Franssen, H. J. H., Canty, M., and Vereecken, H.: Hydraulic parameter estimation by remotely-sensed top soil moisture observations with the particle filter, J. Hydrol., 399, 410–421, https://doi.org/10.1016/j.jhydrol.2011.01.020, 2011.
Moradkhani, H.: Hydrologic remote sensing and land surface data assimilation, Sensors, 8, 2986–3004, https://doi.org/10.3390/S8052986, 2008.
Naeimi, V., Scipal, K., Bartalis, Z., Hasenauer, S., and Wagner, W.: An Improved Soil Moisture Retrieval Algorithm for ERS and METOP Scatterometer Observations, IEEE T. Geosci. Remote, 47, 1999–2013, https://doi.org/10.1109/Tgrs.2009.2011617, 2009.
Nie, S., Zhu, J., and Luo, Y.: Simultaneous estimation of land surface scheme states and parameters using the ensemble Kalman filter: identical twin experiments, Hydrol. Earth Syst. Sci., 15, 2437–2457, https://doi.org/10.5194/hess-15-2437-2011, 2011.
Niu, G. Y., Yang, Z. L., Dickinson, R. E., Gulden, L. E., and Su, H.: Development of a simple groundwater model for use in climate models and evaluation with Gravity Recovery and Climate Experiment data, J. Geophys. Res.-Atmos., 112, D07103, https://doi.org/10.1029/2006jd007522, 2007.
Njoku, E. G. and Chan, S. K.: Vegetation and surface roughness effects on AMSR-E land observations, Remote Sens. Environ., 100, 190–199, https://doi.org/10.1016/j.rse.2005.10.017, 2006.
Oleson, K. W., Lawrence, D. M., Gordon, B., Flanner, M. G., Kluzek, E., Peter, J., Levis, S., Swenson, S. C., Thornton, E., Feddema, J., and Others: Technical description of version 4.0 of the Community Land Model (CLM), NCAR Technical Note NCAR/TN-478+STR, National Center for Atmospheric Research, Boulder, CO, 257 pp., 2010.
Oliphant, T.: A Bayesian perspective on estimating mean, variance, and standard-deviation from data, http://hdl.handle.net/1877/438 (last access: May 2012), 2006.
Pan, M. and Wood, E. F.: Impact of Accuracy, Spatial Availability, and Revisit Time of Satellite-Derived Surface Soil Moisture in a Multiscale Ensemble Data Assimilation System, IEEE J.-Stars, 3, 49–56, https://doi.org/10.1109/Jstars.2010.2040585, 2010.
Pellenq, J., Kalma, J., Boulet, G., Saulnier, G. M., Wooldridge, S., Kerr, Y., and Chehbouni, A.: A disaggregation scheme for soil moisture based on topography and soil depth, J. Hydrol., 276, 112–127, https://doi.org/10.1016/S0022-1694(03)00066-0, 2003.
Reichle, R. H. and Koster, R. D.: Assessing the impact of horizontal error correlations in background fields on soil moisture estimation, J. Hydrometeorol., 4, 1229–1242, 2003.
Reichle, R. H., Koster, R. D., Liu, P., Mahanama, S. P. P., Njoku, E. G., and Owe, M.: Comparison and assimilation of global soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) and the Scanning Multichannel Microwave Radiometer (SMMR), J. Geophys. Res.-Atmos., 112, D09108, https://doi.org/10.1029/2006jd008033, 2007.
Reichle, R. H., Crow, W. T., Koster, R. D., Sharif, H. O., and Mahanama, S. P. P.: Contribution of soil moisture retrievals to land data assimilation products, Geophys. Res. Lett., 35, L01404, https://doi.org/10.1029/2007gl031986, 2008.
Reichle, R. H., Kumar, S. V., Mahanama, S. P. P., Koster, R. D., and Liu, Q.: Assimilation of Satellite-Derived Skin Temperature Observations into Land Surface Models, J. Hydrometeorol., 11, 1103–1122, https://doi.org/10.1175/2010jhm1262.1, 2010.
Ribeiro Jr., P. J. and Diggle, P. J.: geoR: A package for geostatistical analysis, R. News, 1, 14–18, 2001.
Rodell, M., Houser, P. R., Jambor, U., Gottschalck, J., Mitchell, K., Meng, C. J., Arsenault, K., Cosgrove, B., Radakovich, J., Bosilovich, M., Entin, J. K., Walker, J. P., Lohmann, D., and Toll, D.: The global land data assimilation system, B. Am. Meteorol. Soc., 85, 381–394, https://doi.org/10.1175/Bams-85-3-381, 2004.
Ryu, D. and Famiglietti, J. S.: Multi-scale spatial correlation and scaling behavior of surface soil moisture, Geophys. Res. Lett., 33, L08404, https://doi.org/10.1029/2006gl025831, 2006.
Skou, N., Misra, S., Balling, J. E., Kristensen, S. S., and Sobjaerg, S. S.: L-Band RFI as Experienced During Airborne Campaigns in Preparation for SMOS, IEEE T. Geosci. Remote, 48, 1398–1407, https://doi.org/10.1109/Tgrs.2009.2031637, 2010.
Tian, X. J., Xie, Z. H., Dai, A. G., Jia, B. H., and Shi, C. X.: A microwave land data assimilation system: Scheme and preliminary evaluation over China, J. Geophys. Res.-Atmos., 115, D21113, https://doi.org/10.1029/2010jd014370, 2010.
Townshend, J. R. G., Justice, C. O., Gurney, C., and McManus, J.: The impact of misregistration on change detection, IEEE T. Geosci. Remote, 30, 1054–1060, https://doi.org/10.1109/36.175340, 1992.
Wan, Z. and Li, Z. L.: Radiance-based validation of the V5 MODIS land-surface temperature product, Int. J. Remote Sens., 29, 5373–5395, https://doi.org/10.1080/01431160802036565, 2008.
Whitaker, J. S. and Hamill, T. M.: Ensemble data assimilation without perturbed observations, Mon. Weather Rev., 130, 1913–1924, 2002.
Whitaker, J. S., Hamill, T. M., Wei, X., Song, Y. C., and Toth, Z.: Ensemble data assimilation with the NCEP Global Forecast System, Mon. Weather Rev., 136, 463–482, https://doi.org/10.1175/2007mwr2018.1, 2008.
Xu, T. R., Liang, S. L., and Liu, S. M.: Estimating turbulent fluxes through assimilation of geostationary operational environmental satellites data using ensemble Kalman filter, J. Geophys. Res.-Atmos., 116, D09109, https://doi.org/10.1029/2010jd015150, 2011.
Yang, K., Koike, T., Kaihotsu, I., and Qin, J.: Validation of a Dual-Pass Microwave Land Data Assimilation System for Estimating Surface Soil Moisture in Semiarid Regions, J. Hydrometeorol., 10, 780–793, https://doi.org/10.1175/2008jhm1065.1, 2009.
Yilmaz, M. T., DelSole, T., and Houser, P. R.: Improving Land Data Assimilation Performance with a Water Budget Constraint, J. Hydrometeorol., 12, 1040–1055, https://doi.org/10.1175/2011jhm1346.1, 2011.
