Articles | Volume 22, issue 8
https://doi.org/10.5194/hess-22-4329-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-22-4329-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Aug 2018
Research article |
| 16 Aug 2018
| 16 Aug 2018
Evaluation of Doppler radar and GTS data assimilation for NWP rainfall prediction of an extreme summer storm in northern China: from the hydrological perspective
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing, 100038, China
Jiyang Tian
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing, 100038, China
Denghua Yan
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing, 100038, China
Chuanzhe Li
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing, 100038, China
Fuliang Yu
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing, 100038, China
Feifei Shen
Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science & Technology, Nanjing, 210044, China
Related authors
Jiyang Tian, Jia Liu, Yang Wang, Wei Wang, Chuanzhe Li, and Chunqi Hu
Hydrol. Earth Syst. Sci., 24, 3933–3949, https://doi.org/10.5194/hess-24-3933-2020, https://doi.org/10.5194/hess-24-3933-2020, 2020
Short summary
Short summary
The aim of this study is to explore the appropriate coupling scale of the coupled atmospheric–hydrologic modeling system, which is established by the Weather Research and Forecasting (WRF) model and the gridded Hebei model with different sizes. The results show that the flood simulation results may not always be improved with higher-dimension precision and a more complicated system, and the grid size selection has a strong relationship with the rainfall evenness.
Qingtai Qiu, Jia Liu, Chuanzhe Li, Xinzhe Yu, and Yang Wang
Proc. IAHS, 379, 249–253, https://doi.org/10.5194/piahs-379-249-2018, https://doi.org/10.5194/piahs-379-249-2018, 2018
Jiyang Tian, Jia Liu, Denghua Yan, Chuanzhe Li, and Fuliang Yu
Nat. Hazards Earth Syst. Sci., 17, 563–579, https://doi.org/10.5194/nhess-17-563-2017, https://doi.org/10.5194/nhess-17-563-2017, 2017
Short summary
Short summary
Accurately simulating and predicting the precipitation by numerical weather prediction is a difficult task for medium-sized catchments in semi-humid regions. This study shows that using multiphysics ensembles is a good method to reduce the uncertainties of rainfall simulation. This paper provides more guidance for choosing the physical parameterizations for accurate rainfall simulations of different storm types in semi-humid regions.
J. Liu and D. Han
Hydrol. Earth Syst. Sci., 17, 3639–3659, https://doi.org/10.5194/hess-17-3639-2013, https://doi.org/10.5194/hess-17-3639-2013, 2013
J. Liu, M. Bray, and D. Han
Hydrol. Earth Syst. Sci., 17, 3095–3110, https://doi.org/10.5194/hess-17-3095-2013, https://doi.org/10.5194/hess-17-3095-2013, 2013
Keke Zhao, Denghua Yan, Tianling Qin, Chenhao Li, Dingzhi Peng, and Yifan Song
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-291, https://doi.org/10.5194/essd-2025-291, 2025
Preprint under review for ESSD
Short summary
Short summary
This study presents a high-quality daily weather dataset for all of China from 1961 to 2021, including air temperature, atmospheric pressure, relative humidity, and sunshine duration. It was produced using a reconstruction framework that combines thousands of ground observations with landform and elevation data. The dataset provides consistent weather information even in mountainous regions and supports studies on land surface and water processes, climate change, and environmental impacts.
Ying Li, Chenghao Wang, Ru Huang, Denghua Yan, Hui Peng, and Shangbin Xiao
Hydrol. Earth Syst. Sci., 26, 6413–6426, https://doi.org/10.5194/hess-26-6413-2022, https://doi.org/10.5194/hess-26-6413-2022, 2022
Short summary
Short summary
Spatial quantification of oceanic moisture contribution to the precipitation over the Tibetan Plateau (TP) contributes to the reliable assessments of regional water resources and the interpretation of paleo archives in the region. Based on atmospheric reanalysis datasets and numerical moisture tracking, this work reveals the previously underestimated oceanic moisture contributions brought by the westerlies in winter and the overestimated moisture contributions from the Indian Ocean in summer.
Baisha Weng, Zhaoyu Dong, Yuheng Yang, Denghua Yan, Mengyu Li, and Yuhang Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2022-1290, https://doi.org/10.5194/egusphere-2022-1290, 2022
Preprint archived
Short summary
Short summary
The study selected a structural equation model to construct the turnover rate of amino sugars with soil physicochemical properties and extracellular enzymes under the warming and increased precipitation scenarios. The results of this study answer the mechanism of action of warming and precipitation on the effect of soil amino sugars which will play an important scientific and technical support role in the development of plateau agriculture and carbon and nitrogen cycles.
Tongtiegang Zhao, Haoling Chen, Yu Tian, Denghua Yan, Weixin Xu, Huayang Cai, Jiabiao Wang, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 26, 4233–4249, https://doi.org/10.5194/hess-26-4233-2022, https://doi.org/10.5194/hess-26-4233-2022, 2022
Short summary
Short summary
This paper develops a novel set operations of coefficients of determination (SOCD) method to explicitly quantify the overlapping and differing information for GCM forecasts and ENSO teleconnection. Specifically, the intersection operation of the coefficient of determination derives the overlapping information for GCM forecasts and the Niño3.4 index, and then the difference operation determines the differing information in GCM forecasts (Niño3.4 index) from the Niño3.4 index (GCM forecasts).
Ying Li, Chenghao Wang, Hui Peng, Shangbin Xiao, and Denghua Yan
Hydrol. Earth Syst. Sci., 25, 4759–4772, https://doi.org/10.5194/hess-25-4759-2021, https://doi.org/10.5194/hess-25-4759-2021, 2021
Short summary
Short summary
Precipitation change in the Three Gorges Reservoir Region (TGRR) plays a critical role in the operation and regulation of the Three Gorges Dam and the protection of residents and properties. We investigated the long-term contribution of moisture sources to precipitation changes in this region with an atmospheric moisture tracking model. We found that southwestern source regions (especially the southeastern tip of the Tibetan Plateau) are the key regions that control TGRR precipitation changes.
Jiyang Tian, Ronghua Liu, Liuqian Ding, Liang Guo, and Bingyu Zhang
Nat. Hazards Earth Syst. Sci., 21, 723–742, https://doi.org/10.5194/nhess-21-723-2021, https://doi.org/10.5194/nhess-21-723-2021, 2021
Short summary
Short summary
A typhoon always comes with heavy rainfall which leads to great loss. The aim of this study is to explore the reasonable use of Doppler radar data assimilation to correct the initial and lateral boundary conditions of the numerical weather prediction (NWP) systems for typhoon rainstorm forecasts at catchment scale. The results show that assimilating radial velocity at a time interval of 1 h can significantly improve the rainfall simulations and outperform the other assimilation modes.
Jiyang Tian, Jia Liu, Yang Wang, Wei Wang, Chuanzhe Li, and Chunqi Hu
Hydrol. Earth Syst. Sci., 24, 3933–3949, https://doi.org/10.5194/hess-24-3933-2020, https://doi.org/10.5194/hess-24-3933-2020, 2020
Short summary
Short summary
The aim of this study is to explore the appropriate coupling scale of the coupled atmospheric–hydrologic modeling system, which is established by the Weather Research and Forecasting (WRF) model and the gridded Hebei model with different sizes. The results show that the flood simulation results may not always be improved with higher-dimension precision and a more complicated system, and the grid size selection has a strong relationship with the rainfall evenness.
Denghua Yan, Baisha Weng, Tianling Qin, Hao Wang, Xiangnan Li, Yuheng Yang, Kun Wang, Zhenyu Lv, Jianwei Wang, Meng Li, Shan He, Fang Liu, Shanshan Liu, Wuxia Bi, Ting Xu, Xiaoqing Shi, Zihao Man, Congwu Sun, Meiyu Liu, Mengke Wang, Yinghou Huang, Haoyu Long, Yongzhen Niu, Batsuren Dorjsuren, Mohammed Gedefaw, Abel Girma, and Asaminew Abiyu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2019-224, https://doi.org/10.5194/essd-2019-224, 2020
Publication in ESSD not foreseen
Short summary
Short summary
This paper provides a complete data set of global water withdrawal. There is almost no continuous long series of water withdrawal data globally. Moreover, most of the data released by international organizations is based on national scale and lacks finer regional data. Therefore, appropriate methods are needed to modify the data. This dataset has important practical significance in promoting the harmonious and sustainable development of economy and resources of the world.
Wuxia Bi, Baisha Weng, Denghua Yan, Meng Li, Zhilei Yu, Lin Wang, and Hao Wang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-185, https://doi.org/10.5194/hess-2019-185, 2019
Preprint withdrawn
Short summary
Short summary
This study focuses on solving the
land useand
water usecompetitions between lake-marsh wetland system and its surrounding socio-economic system, also inside the system. An optimal lake-marsh pattern determination method was proposed on considering the ecological services values and water shortage amount. We explored the optimal lake-marsh pattern in both annual and monthly scales. This study could provide references for the ecological spatial management and ecological water control.
Qingtai Qiu, Jia Liu, Chuanzhe Li, Xinzhe Yu, and Yang Wang
Proc. IAHS, 379, 249–253, https://doi.org/10.5194/piahs-379-249-2018, https://doi.org/10.5194/piahs-379-249-2018, 2018
Jiyang Tian, Jia Liu, Denghua Yan, Chuanzhe Li, and Fuliang Yu
Nat. Hazards Earth Syst. Sci., 17, 563–579, https://doi.org/10.5194/nhess-17-563-2017, https://doi.org/10.5194/nhess-17-563-2017, 2017
Short summary
Short summary
Accurately simulating and predicting the precipitation by numerical weather prediction is a difficult task for medium-sized catchments in semi-humid regions. This study shows that using multiphysics ensembles is a good method to reduce the uncertainties of rainfall simulation. This paper provides more guidance for choosing the physical parameterizations for accurate rainfall simulations of different storm types in semi-humid regions.
B. S. Weng, D. H. Yan, H. Wang, J. H. Liu, Z. Y. Yang, T. L. Qin, and J. Yin
Nat. Hazards Earth Syst. Sci., 15, 1889–1906, https://doi.org/10.5194/nhess-15-1889-2015, https://doi.org/10.5194/nhess-15-1889-2015, 2015
B. B. Huang, D. H. Yan, H. Wang, B. F. Cheng, and X. H. Cui
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-14463-2013, https://doi.org/10.5194/hessd-10-14463-2013, 2013
Manuscript not accepted for further review
J. Liu and D. Han
Hydrol. Earth Syst. Sci., 17, 3639–3659, https://doi.org/10.5194/hess-17-3639-2013, https://doi.org/10.5194/hess-17-3639-2013, 2013
J. Liu, M. Bray, and D. Han
Hydrol. Earth Syst. Sci., 17, 3095–3110, https://doi.org/10.5194/hess-17-3095-2013, https://doi.org/10.5194/hess-17-3095-2013, 2013
D. H. Yan, D. Wu, R. Huang, L. N. Wang, and G. Y. Yang
Hydrol. Earth Syst. Sci., 17, 2859–2871, https://doi.org/10.5194/hess-17-2859-2013, https://doi.org/10.5194/hess-17-2859-2013, 2013
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
The role of land–atmosphere coupling in subseasonal surface air temperature prediction across the contiguous United States
Barriers to urban hydrometeorological simulation: a review
Global catalog of soil moisture droughts over the past four decades
Probabilistic precipitation downscaling for ungauged mountain sites: a pilot study for the Hindu Kush Himalaya
Implementation of global soil databases in the Noah-MP model and the effects on simulated mean and extreme soil hydrothermal changes
Skilful probabilistic predictions of UK flood risk months ahead using a large-sample machine learning model trained on multimodel ensemble climate forecasts
Towards a robust hydrologic data assimilation system for hurricane-induced river flow forecasting
Enhanced evaluation of hourly and daily extreme precipitation in Norway from convection-permitting models at regional and local scales
Deep-learning-based sub-seasonal precipitation and streamflow ensemble forecasting over the source region of the Yangtze River
High-resolution land surface modelling over Africa: the role of uncertain soil properties in combination with forcing temporal resolution
Investigating the global and regional response of drought to idealized deforestation using multiple global climate models
Distribution, trends, and drivers of flash droughts in the United Kingdom
Are dependencies of extreme rainfall on humidity more reliable in convection-permitting climate models?
Leveraging a radar-based disdrometer network to develop a probabilistic precipitation phase model in eastern Canada
Assessment of seasonal soil moisture forecasts over the Central Mediterranean
Saudi Rainfall (SaRa): Hourly 0.1° Gridded Rainfall (1979–Present) for Saudi Arabia via Machine Learning Fusion of Satellite and Model Data
Do land models miss key soil hydrological processes controlling soil moisture memory?
Observation-driven model for calculating water-harvesting potential from advective fog in (semi-)arid coastal regions
Review of gridded climate products and their use in hydrological analyses reveals overlaps, gaps, and the need for a more objective approach to selecting model forcing datasets
Downscaling the probability of heavy rainfall over the Nordic countries
Modelling convective cell life cycles with a copula-based approach
Downscaling precipitation over High-mountain Asia using multi-fidelity Gaussian processes: improved estimates from ERA5
Mapping soil moisture across the UK: assimilating cosmic-ray neutron sensors, remotely sensed indices, rainfall radar and catchment water balance data in a Bayesian hierarchical model
Informativeness of teleconnections in local and regional frequency analysis of rainfall extremes
Assessing rainfall radar errors with an inverse stochastic modelling framework
Enhanced hydrological modelling with the WRF-Hydro lake/reservoir module at Convection-Permitting scale: a case study of the Tana River basin in East Africa
Multi-objective calibration and evaluation of the ORCHIDEE land surface model over France at high resolution
Spatiotemporal responses of runoff to climate change in the southern Tibetan Plateau
FROSTBYTE: a reproducible data-driven workflow for probabilistic seasonal streamflow forecasting in snow-fed river basins across North America
Storyline Analytical Framework for Understanding Future Severe Low-Water Episodes and Their Consequences
Assessing multivariate bias corrections of climate simulations on various impact models under climate change
On the combined use of rain gauges and GPM IMERG satellite rainfall products for hydrological modelling: impact assessment of the cellular-automata-based methodology in the Tanaro River basin in Italy
An increase in the spatial extent of European floods over the last 70 years
140-year daily ensemble streamflow reconstructions over 661 catchments in France
The agricultural expansion in South America's Dry Chaco: regional hydroclimate effects
Machine-learning-constrained projection of bivariate hydrological drought magnitudes and socioeconomic risks over China
Improving runoff simulation in the Western United States with Noah-MP and VIC models
Spatial variability in the seasonal precipitation lapse rates in complex topographical regions – application in France
Assessing downscaling methods to simulate hydrologically relevant weather scenarios from a global atmospheric reanalysis: case study of the upper Rhône River (1902–2009)
Global total precipitable water variations and trends over the period 1958–2021
Assessing decadal- to centennial-scale nonstationary variability in meteorological drought trends
Identification of compound drought and heatwave events on a daily scale and across four seasons
Potential for historically unprecedented Australian droughts from natural variability and climate change
Flood risk assessment for Indian sub-continental river basins
Key ingredients in regional climate modelling for improving the representation of typhoon tracks and intensities
Divergent future drought projections in UK river flows and groundwater levels
Predicting extreme sub-hourly precipitation intensification based on temperature shifts
Hydroclimatic processes as the primary drivers of the Early Khvalynian transgression of the Caspian Sea: new developments
Accounting for hydroclimatic properties in flood frequency analysis procedures
Understanding the influence of “hot” models in climate impact studies: a hydrological perspective
Yuna Lim, Andrea M. Molod, Randal D. Koster, and Joseph A. Santanello
Hydrol. Earth Syst. Sci., 29, 3435–3445, https://doi.org/10.5194/hess-29-3435-2025, https://doi.org/10.5194/hess-29-3435-2025, 2025
Short summary
Short summary
To better utilize a given set of predictions, identifying “forecasts of opportunity” is valuable as this helps anticipate when prediction skill will be higher. This study shows that when strong land–atmosphere (L–A) coupling is detected 3–4 weeks into a forecast, the surface air temperature prediction skill at this lead time increases across the Midwest and northern Great Plains. Regions experiencing strong L–A coupling exhibit warm and dry anomalies, enhancing predictions of abnormally warm events.
Xuan Chen, Job Augustijn van der Werf, Arjan Droste, Miriam Coenders-Gerrits, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 29, 3447–3480, https://doi.org/10.5194/hess-29-3447-2025, https://doi.org/10.5194/hess-29-3447-2025, 2025
Short summary
Short summary
The review highlights the need to integrate urban land surface and hydrological models to better predict and manage compound climate events in cities. We find that inadequate representation of water surfaces, hydraulic systems and detailed building representations are key areas for improvement in future models. Coupled models show promise but face challenges at regional and neighbourhood scales. Interdisciplinary communication is crucial to enhance urban hydrometeorological simulations.
Jan Řehoř, Rudolf Brázdil, Oldřich Rakovec, Martin Hanel, Milan Fischer, Rohini Kumar, Jan Balek, Markéta Poděbradská, Vojtěch Moravec, Luis Samaniego, Yannis Markonis, and Miroslav Trnka
Hydrol. Earth Syst. Sci., 29, 3341–3358, https://doi.org/10.5194/hess-29-3341-2025, https://doi.org/10.5194/hess-29-3341-2025, 2025
Short summary
Short summary
We present a robust method for identification and classification of global land drought events (GLDEs) based on soil moisture. Two models were used to calculate soil moisture and delimit soil drought over global land from 1980–2022, with clusters of 775 and 630 GLDEs. Using four spatiotemporal and three motion-related characteristics, we categorized GLDEs into seven severity and seven dynamic categories. The frequency of GLDEs has generally increased in recent decades.
Marc Girona-Mata, Andrew Orr, Martin Widmann, Daniel Bannister, Ghulam Hussain Dars, Scott Hosking, Jesse Norris, David Ocio, Tony Phillips, Jakob Steiner, and Richard E. Turner
Hydrol. Earth Syst. Sci., 29, 3073–3100, https://doi.org/10.5194/hess-29-3073-2025, https://doi.org/10.5194/hess-29-3073-2025, 2025
Short summary
Short summary
We introduce a novel method for improving daily precipitation maps in mountain regions and pilot it across three basins in the Hindu Kush Himalaya (HKH). The approach leverages climate model and weather station data, along with statistical or machine learning techniques. Our results show that this approach outperforms traditional methods, especially in remote ungauged areas, suggesting that it could be used to improve precipitation maps across much of the HKH, as well as other mountain regions.
Kazeem Abiodun Ishola, Gerald Mills, Ankur Prabhat Sati, Benjamin Obe, Matthias Demuzere, Deepak Upreti, Gourav Misra, Paul Lewis, Daire Walsh, Tim McCarthy, and Rowan Fealy
Hydrol. Earth Syst. Sci., 29, 2551–2582, https://doi.org/10.5194/hess-29-2551-2025, https://doi.org/10.5194/hess-29-2551-2025, 2025
Short summary
Short summary
Global soil information introduces uncertainty into models that simulate soil hydrothermal changes. Using the Noah with Multiparameterization (Noah-MP) model with two different global soil datasets, we find under-represented soil properties in wet loam, causing a dry bias in soil moisture. This bias is more pronounced and drought categories are more severe in the SoilGrids dataset. We conclude that models should incorporate detailed, region-specific soil information to minimize model uncertainties.
Simon Moulds, Louise Slater, Louise Arnal, and Andrew W. Wood
Hydrol. Earth Syst. Sci., 29, 2393–2406, https://doi.org/10.5194/hess-29-2393-2025, https://doi.org/10.5194/hess-29-2393-2025, 2025
Short summary
Short summary
Seasonal streamflow forecasts are an important component of flood risk management. Here, we train and test a machine learning model to predict the monthly maximum daily streamflow up to 4 months ahead. We train the model on precipitation and temperature forecasts to produce probabilistic hindcasts for 579 stations across the UK for the period 2004–2016. We show skilful results up to 4 months ahead in many locations, although, in general, the skill declines with increasing lead time.
Peyman Abbaszadeh, Fatemeh Gholizadeh, Keyhan Gavahi, and Hamid Moradkhani
Hydrol. Earth Syst. Sci., 29, 2407–2427, https://doi.org/10.5194/hess-29-2407-2025, https://doi.org/10.5194/hess-29-2407-2025, 2025
Short summary
Short summary
The Hybrid Ensemble and Variational Data Assimilation framework for Environmental Systems (HEAVEN) enhances flood predictions by refining hydrologic models through improved data integration and uncertainty management. Tested in three southeastern US watersheds during hurricanes, HEAVEN assimilates real-time United States Geological Survey (USGS) streamflow data, boosting forecast accuracy.
Kun Xie, Lu Li, Hua Chen, Stephanie Mayer, Andreas Dobler, Chong-Yu Xu, and Ozan Mert Göktürk
Hydrol. Earth Syst. Sci., 29, 2133–2152, https://doi.org/10.5194/hess-29-2133-2025, https://doi.org/10.5194/hess-29-2133-2025, 2025
Short summary
Short summary
We compared hourly and daily extreme precipitation across Norway from HARMONIE Climate models at convection-permitting 3 km (HCLIM3) and 12 km (HCLIM12) resolutions. HCLIM3 more accurately captures the extremes in most regions and seasons (except in summer). Its advantages are more pronounced for hourly extremes than for daily extremes. The results highlight the value of convection-permitting models in improving extreme-precipitation predictions and in helping the local society brace for extreme weather.
Ningpeng Dong, Haoran Hao, Mingxiang Yang, Jianhui Wei, Shiqin Xu, and Harald Kunstmann
Hydrol. Earth Syst. Sci., 29, 2023–2042, https://doi.org/10.5194/hess-29-2023-2025, https://doi.org/10.5194/hess-29-2023-2025, 2025
Short summary
Short summary
Hydrometeorological forecasting is crucial for managing water resources and mitigating extreme weather events, yet current long-term forecast products are often embedded with uncertainties. We develop a deep-learning-based modelling framework to improve 30 d rainfall and streamflow forecasts by combining advanced neural networks and physical models. With the flow forecast error reduced by up to 33 %, the framework has the potential to enhance water management and disaster prevention.
Bamidele Oloruntoba, Stefan Kollet, Carsten Montzka, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 29, 1659–1683, https://doi.org/10.5194/hess-29-1659-2025, https://doi.org/10.5194/hess-29-1659-2025, 2025
Short summary
Short summary
We studied how soil and weather data affect land model simulations over Africa. By combining soil data processed in different ways with weather data of varying time intervals, we found that weather inputs had a greater impact on water processes than soil data type. However, the way soil data were processed became crucial when paired with high-frequency weather inputs, showing that detailed weather data can improve local and regional predictions of how water moves and interacts with the land.
Yan Li, Bo Huang, Chunping Tan, Xia Zhang, Francesco Cherubini, and Henning W. Rust
Hydrol. Earth Syst. Sci., 29, 1637–1658, https://doi.org/10.5194/hess-29-1637-2025, https://doi.org/10.5194/hess-29-1637-2025, 2025
Short summary
Short summary
Deforestation has a significant impact on climate, yet its effects on drought remain less understood. This study investigates how deforestation affects drought across various climate zones and timescales. Findings indicate that deforestation leads to drier conditions in tropical regions and wetter conditions in arid areas, with minimal effects in temperate zones. Long-term drought is more affected than short-term drought, offering valuable insights into vegetation–climate interactions.
Iván Noguera, Jamie Hannaford, and Maliko Tanguy
Hydrol. Earth Syst. Sci., 29, 1295–1317, https://doi.org/10.5194/hess-29-1295-2025, https://doi.org/10.5194/hess-29-1295-2025, 2025
Short summary
Short summary
The study provides a detailed characterisation of flash drought in the UK for 1969–2021. The spatio-temporal distribution and trends of flash droughts are highly variable, with important regional and seasonal contrasts. In the UK, flash drought development responds primarily to precipitation variability, while the atmospheric evaporative demand plays a secondary role. We also found that the North Atlantic Oscillation is the main circulation pattern controlling flash drought development.
Geert Lenderink, Nikolina Ban, Erwan Brisson, Ségolène Berthou, Virginia Edith Cortés-Hernández, Elizabeth Kendon, Hayley J. Fowler, and Hylke de Vries
Hydrol. Earth Syst. Sci., 29, 1201–1220, https://doi.org/10.5194/hess-29-1201-2025, https://doi.org/10.5194/hess-29-1201-2025, 2025
Short summary
Short summary
Future extreme rainfall events are influenced by changes in both absolute and relative humidity. The impact of increasing absolute humidity is reasonably well understood, but the role of relative humidity decreases over land remains largely unknown. Using hourly observations from France and the Netherlands, we find that lower relative humidity generally leads to more intense rainfall extremes. This relation is only captured well in recently developed convection-permitting climate models.
Alexis Bédard-Therrien, François Anctil, Julie M. Thériault, Olivier Chalifour, Fanny Payette, Alexandre Vidal, and Daniel F. Nadeau
Hydrol. Earth Syst. Sci., 29, 1135–1158, https://doi.org/10.5194/hess-29-1135-2025, https://doi.org/10.5194/hess-29-1135-2025, 2025
Short summary
Short summary
Precipitation data from an automated observational network in eastern Canada showed a temperature interval where rain and snow could coexist. Random forest models were developed to classify the precipitation phase using meteorological data to evaluate operational applications. The models demonstrated significantly improved phase classification and reduced error compared to benchmark operational models. However, accurate prediction of mixed-phase precipitation remains challenging.
Lorenzo Silvestri, Miriam Saraceni, Bruno Brunone, Silvia Meniconi, Giulia Passadore, and Paolina Bongioannini Cerlini
Hydrol. Earth Syst. Sci., 29, 925–946, https://doi.org/10.5194/hess-29-925-2025, https://doi.org/10.5194/hess-29-925-2025, 2025
Short summary
Short summary
This work demonstrates that seasonal forecasts of soil moisture are a valuable resource for groundwater management in the areas of the Central Mediterranean where longer memory timescales are found. In particular, they show significant correlation coefficients and forecast skill for the deepest soil moisture at 289 cm depth. Wet and dry events can be predicted 6 months in advance, and, in general, dry events are better captured than wet events.
Xuetong Wang, Raied S. Alharbi, Oscar M. Baez-Villanueva, Amy Green, Matthew F. McCabe, Yoshihide Wada, Albert I. J. M. Van Dijk, Muhammad A. Abid, and Hylke Beck
EGUsphere, https://doi.org/10.5194/egusphere-2025-254, https://doi.org/10.5194/egusphere-2025-254, 2025
Short summary
Short summary
Our paper introduces Saudi Rainfall (SaRa), a high-resolution, near real-time rainfall product for the Arabian Peninsula. Using machine learning, SaRa combines multiple satellite and (re)analysis datasets with static predictors, outperforming existing products in the region. With the fast development and continuing growth in water demand over this region, SaRa could help to address water challenges and support resource management.
Mohammad A. Farmani, Ali Behrangi, Aniket Gupta, Ahmad Tavakoly, Matthew Geheran, and Guo-Yue Niu
Hydrol. Earth Syst. Sci., 29, 547–566, https://doi.org/10.5194/hess-29-547-2025, https://doi.org/10.5194/hess-29-547-2025, 2025
Short summary
Short summary
Soil moisture memory (SMM) shows how long soil stays moist after rain, impacting climate and ecosystems. Current models often overestimate SMM, causing inaccuracies in evaporation predictions. We enhanced a land model, Noah-MP, to include better water flow and ponding processes, and we tested it against satellite and field data. This improved model reduced overestimations and enhanced short-term predictions, helping create more accurate climate and weather forecasts.
Felipe Lobos-Roco, Jordi Vilà-Guerau de Arellano, and Camilo del Río
Hydrol. Earth Syst. Sci., 29, 109–125, https://doi.org/10.5194/hess-29-109-2025, https://doi.org/10.5194/hess-29-109-2025, 2025
Short summary
Short summary
Water resources are fundamental for the social, economic, and natural development of (semi-)arid regions. Precipitation decreases due to climate change obligate us to find new water resources. Fog harvesting (FH) emerges as a complementary resource in regions where it is abundant but untapped. This research proposes a model to estimate FH potential in coastal (semi-)arid regions. This model could have broader applicability worldwide in regions where FH could be a viable water source.
Kyle R. Mankin, Sushant Mehan, Timothy R. Green, and David M. Barnard
Hydrol. Earth Syst. Sci., 29, 85–108, https://doi.org/10.5194/hess-29-85-2025, https://doi.org/10.5194/hess-29-85-2025, 2025
Short summary
Short summary
We assess 63 gridded ground (G), satellite (S), and reanalysis (R) climate datasets. Higher-density station data and less-hilly terrain improved climate data. In mountainous and humid regions, dataset types performed similarly; however, R outperformed G when underlying data had low station density. G outperformed S or R datasets, although better streamflow modeling did not always follow. Hydrologic analyses need datasets that better represent climate variable dependencies and complex topography.
Rasmus E. Benestad, Kajsa M. Parding, and Andreas Dobler
Hydrol. Earth Syst. Sci., 29, 45–65, https://doi.org/10.5194/hess-29-45-2025, https://doi.org/10.5194/hess-29-45-2025, 2025
Short summary
Short summary
We present a new method to calculate the chance of heavy downpour and the maximum rainfall expected over a 25-year period. It is designed to analyse global climate models' reproduction of past and future climates. For the Nordic countries, it projects a wetter climate in the future with increased intensity but not necessarily more wet days. The analysis also shows that rainfall intensity is sensitive to future greenhouse gas emissions, while the number of wet days appears to be less affected.
Chien-Yu Tseng, Li-Pen Wang, and Christian Onof
Hydrol. Earth Syst. Sci., 29, 1–25, https://doi.org/10.5194/hess-29-1-2025, https://doi.org/10.5194/hess-29-1-2025, 2025
Short summary
Short summary
This study presents a new algorithm to model convective storms. We used advanced tracking methods to analyse 165 storm events in Birmingham (UK) and reconstruct storm cell life cycles. We found that cell properties like intensity and size are interrelated and vary over time. The new algorithm, based on vine copulas, accurately simulates these properties and their evolution. It also integrates an exponential shape function for realistic rainfall patterns, enhancing its hydrological applicability.
Kenza Tazi, Andrew Orr, Javier Hernandez-González, Scott Hosking, and Richard E. Turner
Hydrol. Earth Syst. Sci., 28, 4903–4925, https://doi.org/10.5194/hess-28-4903-2024, https://doi.org/10.5194/hess-28-4903-2024, 2024
Short summary
Short summary
This work aims to improve the understanding of precipitation patterns in High-mountain Asia, a crucial water source for around 1.9 billion people. Through a novel machine learning method, we generate high-resolution precipitation predictions, including the likelihoods of floods and droughts. Compared to state-of-the-art methods, our method is simpler to implement and more suitable for small datasets. The method also shows accuracy comparable to or better than existing benchmark datasets.
Peter E. Levy and the COSMOS-UK team
Hydrol. Earth Syst. Sci., 28, 4819–4836, https://doi.org/10.5194/hess-28-4819-2024, https://doi.org/10.5194/hess-28-4819-2024, 2024
Short summary
Short summary
Having accurate up-to-date maps of soil moisture is important for many purposes. However, current modelled and remotely sensed maps are rather coarse and not very accurate. Here, we demonstrate a simple but accurate approach that is closely linked to direct measurements of soil moisture at a network sites across the UK, to the water balance (precipitation minus drainage and evaporation) measured at a large number of catchments (1212) and to remotely sensed satellite estimates.
Andrea Magnini, Valentina Pavan, and Attilio Castellarin
EGUsphere, https://doi.org/10.5194/egusphere-2024-3261, https://doi.org/10.5194/egusphere-2024-3261, 2024
Short summary
Short summary
This study describes a new methodology to identify regional structures in the dependence of extreme rainfall on global climate indexes. The study area is north-central Italy, but the methods are highly adaptable to other regions. We observe that the Western Mediterranean Oscillation Index has a strong influence, whose geographical pattern is in line with other studies. We show also that the use of the Index may improve the estimation of the extreme rainfall depth with a given probability.
Amy C. Green, Chris Kilsby, and András Bárdossy
Hydrol. Earth Syst. Sci., 28, 4539–4558, https://doi.org/10.5194/hess-28-4539-2024, https://doi.org/10.5194/hess-28-4539-2024, 2024
Short summary
Short summary
Weather radar is a crucial tool in rainfall estimation, but radar rainfall estimates are subject to many error sources, with the true rainfall field unknown. A flexible model for simulating errors relating to the radar rainfall estimation process is implemented, inverting standard processing methods. This flexible and efficient model performs well in generating realistic weather radar images visually for a large range of event types.
Ling Zhang, Lu Li, Zhongshi Zhang, Joël Arnault, Stefan Sobolowski, Anthony Musili Mwanthi, Pratik Kad, Mohammed Abdullahi Hassan, Tanja Portele, and Harald Kunstmann
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-278, https://doi.org/10.5194/hess-2024-278, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
To address challenges related to unreliable hydrological simulations, we present an enhanced hydrological simulation with a refined climate model and a more comprehensive hydrological model. The model with the two parts outperforms that without, especially in migrating bias in peak flow and dry-season flow. Our findings highlight the enhanced hydrological simulation capability with the refined climate and lake module contributing 24 % and 76 % improvement, respectively.
Peng Huang, Agnès Ducharne, Lucia Rinchiuso, Jan Polcher, Laure Baratgin, Vladislav Bastrikov, and Eric Sauquet
Hydrol. Earth Syst. Sci., 28, 4455–4476, https://doi.org/10.5194/hess-28-4455-2024, https://doi.org/10.5194/hess-28-4455-2024, 2024
Short summary
Short summary
We conducted a high-resolution hydrological simulation from 1959 to 2020 across France. We used a simple trial-and-error calibration to reduce the biases of the simulated water budget compared to observations. The selected simulation satisfactorily reproduces water fluxes, including their spatial contrasts and temporal trends. This work offers a reliable historical overview of water resources and a robust configuration for climate change impact analysis at the nationwide scale of France.
He Sun, Tandong Yao, Fengge Su, Wei Yang, and Deliang Chen
Hydrol. Earth Syst. Sci., 28, 4361–4381, https://doi.org/10.5194/hess-28-4361-2024, https://doi.org/10.5194/hess-28-4361-2024, 2024
Short summary
Short summary
Our findings show that runoff in the Yarlung Zangbo (YZ) basin is primarily driven by rainfall, with the largest glacier runoff contribution in the downstream sub-basin. Annual runoff increased in the upper stream but decreased downstream due to varying precipitation patterns. It is expected to rise throughout the 21st century, mainly driven by increased rainfall.
Louise Arnal, Martyn P. Clark, Alain Pietroniro, Vincent Vionnet, David R. Casson, Paul H. Whitfield, Vincent Fortin, Andrew W. Wood, Wouter J. M. Knoben, Brandi W. Newton, and Colleen Walford
Hydrol. Earth Syst. Sci., 28, 4127–4155, https://doi.org/10.5194/hess-28-4127-2024, https://doi.org/10.5194/hess-28-4127-2024, 2024
Short summary
Short summary
Forecasting river flow months in advance is crucial for water sectors and society. In North America, snowmelt is a key driver of flow. This study presents a statistical workflow using snow data to forecast flow months ahead in North American snow-fed rivers. Variations in the river flow predictability across the continent are evident, raising concerns about future predictability in a changing (snow) climate. The reproducible workflow hosted on GitHub supports collaborative and open science.
Gabriel Rondeau-Genesse, Louis-Philippe Caron, Kristelle Audet, Laurent Da Silva, Daniel Tarte, Rachel Parent, Élise Comeau, and Dominic Matte
EGUsphere, https://doi.org/10.5194/egusphere-2024-2595, https://doi.org/10.5194/egusphere-2024-2595, 2024
Short summary
Short summary
The 2021 drought in Quebec showcased the province’s potential vulnerability. This study uses a storyline approach to explore impacts of future extreme droughts under +2 °C and +3 °C warming scenarios. By combining regional climate and hydrological simulations, it highlights the potential for severe water deficits. Collaboration with water management experts helped project the impacts of those future extreme droughts and their consequences for ecosystems and human activities.
Denis Allard, Mathieu Vrac, Bastien François, and Iñaki García de Cortázar-Atauri
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-102, https://doi.org/10.5194/hess-2024-102, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Atmospheric variables from climate models often present biases relative to the past. In order to use these models to assess the impact of climate change on processes of interest, it is necessary to correct these biases. We tested several Multivariate Bias Correction Methods (MBCMs) for 5 physical variables that are input variables for 4 process models. We provide recommendations regarding the use of MBCMs when multivariate and time dependent processes are involved.
Annalina Lombardi, Barbara Tomassetti, Valentina Colaiuda, Ludovico Di Antonio, Paolo Tuccella, Mario Montopoli, Giovanni Ravazzani, Frank Silvio Marzano, Raffaele Lidori, and Giulia Panegrossi
Hydrol. Earth Syst. Sci., 28, 3777–3797, https://doi.org/10.5194/hess-28-3777-2024, https://doi.org/10.5194/hess-28-3777-2024, 2024
Short summary
Short summary
The accurate estimation of precipitation and its spatial variability within a watershed is crucial for reliable discharge simulations. The study is the first detailed analysis of the potential usage of the cellular automata technique to merge different rainfall data inputs to hydrological models. This work shows an improvement in the performance of hydrological simulations when satellite and rain gauge data are merged.
Beijing Fang, Emanuele Bevacqua, Oldrich Rakovec, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 28, 3755–3775, https://doi.org/10.5194/hess-28-3755-2024, https://doi.org/10.5194/hess-28-3755-2024, 2024
Short summary
Short summary
We use grid-based runoff from a hydrological model to identify large spatiotemporally connected flood events in Europe, assess extent trends over the last 70 years, and attribute the trends to different drivers. Our findings reveal a general increase in flood extent, with regional variations driven by diverse factors. The study not only enables a thorough examination of flood events across multiple basins but also highlights the potential challenges arising from changing flood extents.
Alexandre Devers, Jean-Philippe Vidal, Claire Lauvernet, Olivier Vannier, and Laurie Caillouet
Hydrol. Earth Syst. Sci., 28, 3457–3474, https://doi.org/10.5194/hess-28-3457-2024, https://doi.org/10.5194/hess-28-3457-2024, 2024
Short summary
Short summary
Daily streamflow series for 661 near-natural French catchments are reconstructed over 1871–2012 using two ensemble datasets: HydRE and HydREM. They include uncertainties coming from climate forcings, streamflow measurement, and hydrological model error (for HydrREM). Comparisons with other hydrological reconstructions and independent/dependent observations show the added value of the two reconstructions in terms of quality, uncertainty estimation, and representation of extremes.
María Agostina Bracalenti, Omar V. Müller, Miguel A. Lovino, and Ernesto Hugo Berbery
Hydrol. Earth Syst. Sci., 28, 3281–3303, https://doi.org/10.5194/hess-28-3281-2024, https://doi.org/10.5194/hess-28-3281-2024, 2024
Short summary
Short summary
The Gran Chaco is a large, dry forest in South America that has been heavily deforested, particularly in the dry Chaco subregion. This deforestation, mainly driven by the expansion of the agricultural frontier, has changed the land's characteristics, affecting the local and regional climate. The study reveals that deforestation has resulted in reduced precipitation, soil moisture, and runoff, and if intensive agriculture continues, it could make summers in this arid region even drier and hotter.
Rutong Liu, Jiabo Yin, Louise Slater, Shengyu Kang, Yuanhang Yang, Pan Liu, Jiali Guo, Xihui Gu, Xiang Zhang, and Aliaksandr Volchak
Hydrol. Earth Syst. Sci., 28, 3305–3326, https://doi.org/10.5194/hess-28-3305-2024, https://doi.org/10.5194/hess-28-3305-2024, 2024
Short summary
Short summary
Climate change accelerates the water cycle and alters the spatiotemporal distribution of hydrological variables, thus complicating the projection of future streamflow and hydrological droughts. We develop a cascade modeling chain to project future bivariate hydrological drought characteristics over China, using five bias-corrected global climate model outputs under three shared socioeconomic pathways, five hydrological models, and a deep-learning model.
Lu Su, Dennis P. Lettenmaier, Ming Pan, and Benjamin Bass
Hydrol. Earth Syst. Sci., 28, 3079–3097, https://doi.org/10.5194/hess-28-3079-2024, https://doi.org/10.5194/hess-28-3079-2024, 2024
Short summary
Short summary
We fine-tuned the variable infiltration capacity (VIC) and Noah-MP models across 263 river basins in the Western US. We developed transfer relationships to similar basins and extended the fine-tuned parameters to ungauged basins. Both models performed best in humid areas, and the skills improved post-calibration. VIC outperforms Noah-MP in all but interior dry basins following regionalization. VIC simulates annual mean streamflow and high flow well, while Noah-MP performs better for low flows.
Valentin Dura, Guillaume Evin, Anne-Catherine Favre, and David Penot
Hydrol. Earth Syst. Sci., 28, 2579–2601, https://doi.org/10.5194/hess-28-2579-2024, https://doi.org/10.5194/hess-28-2579-2024, 2024
Short summary
Short summary
The increase in precipitation as a function of elevation is poorly understood in areas with complex topography. In this article, the reproduction of these orographic gradients is assessed with several precipitation products. The best product is a simulation from a convection-permitting regional climate model. The corresponding seasonal gradients vary significantly in space, with higher values for the first topographical barriers exposed to the dominant air mass circulations.
Caroline Legrand, Benoît Hingray, Bruno Wilhelm, and Martin Ménégoz
Hydrol. Earth Syst. Sci., 28, 2139–2166, https://doi.org/10.5194/hess-28-2139-2024, https://doi.org/10.5194/hess-28-2139-2024, 2024
Short summary
Short summary
Climate change is expected to increase flood hazard worldwide. The evolution is typically estimated from multi-model chains, where regional hydrological scenarios are simulated from weather scenarios derived from coarse-resolution atmospheric outputs of climate models. We show that two such chains are able to reproduce, from an atmospheric reanalysis, the 1902–2009 discharge variations and floods of the upper Rhône alpine river, provided that the weather scenarios are bias-corrected.
Nenghan Wan, Xiaomao Lin, Roger A. Pielke Sr., Xubin Zeng, and Amanda M. Nelson
Hydrol. Earth Syst. Sci., 28, 2123–2137, https://doi.org/10.5194/hess-28-2123-2024, https://doi.org/10.5194/hess-28-2123-2024, 2024
Short summary
Short summary
Global warming occurs at a rate of 0.21 K per decade, resulting in about 9.5 % K−1 of water vapor response to temperature from 1993 to 2021. Terrestrial areas experienced greater warming than the ocean, with a ratio of 2 : 1. The total precipitable water change in response to surface temperature changes showed a variation around 6 % K−1–8 % K−1 in the 15–55° N latitude band. Further studies are needed to identify the mechanisms leading to different water vapor responses.
Kyungmin Sung, Max C. A. Torbenson, and James H. Stagge
Hydrol. Earth Syst. Sci., 28, 2047–2063, https://doi.org/10.5194/hess-28-2047-2024, https://doi.org/10.5194/hess-28-2047-2024, 2024
Short summary
Short summary
This study examines centuries of nonstationary trends in meteorological drought and pluvial climatology. A novel approach merges tree-ring proxy data (North American Seasonal Precipitation Atlas – NASPA) with instrumental precipitation datasets by temporally downscaling proxy data, correcting biases, and analyzing shared trends in normal and extreme precipitation anomalies. We identify regions experiencing recent unprecedented shifts towards drier or wetter conditions and shifts in seasonality.
Baoying Shan, Niko E. C. Verhoest, and Bernard De Baets
Hydrol. Earth Syst. Sci., 28, 2065–2080, https://doi.org/10.5194/hess-28-2065-2024, https://doi.org/10.5194/hess-28-2065-2024, 2024
Short summary
Short summary
This study developed a convenient and new method to identify the occurrence of droughts, heatwaves, and co-occurring droughts and heatwaves (CDHW) across four seasons. Using this method, we could establish the start and/or end dates of drought (or heatwave) events. We found an increase in the frequency of heatwaves and CDHW events in Belgium caused by climate change. We also found that different months have different chances of CDHW events.
Georgina M. Falster, Nicky M. Wright, Nerilie J. Abram, Anna M. Ukkola, and Benjamin J. Henley
Hydrol. Earth Syst. Sci., 28, 1383–1401, https://doi.org/10.5194/hess-28-1383-2024, https://doi.org/10.5194/hess-28-1383-2024, 2024
Short summary
Short summary
Multi-year droughts have severe environmental and economic impacts, but the instrumental record is too short to characterise multi-year drought variability. We assessed the nature of Australian multi-year droughts using simulations of the past millennium from 11 climate models. We show that multi-decadal
megadroughtsare a natural feature of the Australian hydroclimate. Human-caused climate change is also driving a tendency towards longer droughts in eastern and southwestern Australia.
Urmin Vegad, Yadu Pokhrel, and Vimal Mishra
Hydrol. Earth Syst. Sci., 28, 1107–1126, https://doi.org/10.5194/hess-28-1107-2024, https://doi.org/10.5194/hess-28-1107-2024, 2024
Short summary
Short summary
A large population is affected by floods, which leave their footprints through human mortality, migration, and damage to agriculture and infrastructure, during almost every summer monsoon season in India. Despite the massive damage of floods, sub-basin level flood risk assessment is still in its infancy and needs to be improved. Using hydrological and hydrodynamic models, we reconstructed sub-basin level observed floods for the 1901–2020 period.
Qi Sun, Patrick Olschewski, Jianhui Wei, Zhan Tian, Laixiang Sun, Harald Kunstmann, and Patrick Laux
Hydrol. Earth Syst. Sci., 28, 761–780, https://doi.org/10.5194/hess-28-761-2024, https://doi.org/10.5194/hess-28-761-2024, 2024
Short summary
Short summary
Tropical cyclones (TCs) often cause high economic loss due to heavy winds and rainfall, particularly in densely populated regions such as the Pearl River Delta (China). This study provides a reference to set up regional climate models for TC simulations. They contribute to a better TC process understanding and assess the potential changes and risks of TCs in the future. This lays the foundation for hydrodynamical modelling, from which the cities' disaster management and defence could benefit.
Simon Parry, Jonathan D. Mackay, Thomas Chitson, Jamie Hannaford, Eugene Magee, Maliko Tanguy, Victoria A. Bell, Katie Facer-Childs, Alison Kay, Rosanna Lane, Robert J. Moore, Stephen Turner, and John Wallbank
Hydrol. Earth Syst. Sci., 28, 417–440, https://doi.org/10.5194/hess-28-417-2024, https://doi.org/10.5194/hess-28-417-2024, 2024
Short summary
Short summary
We studied drought in a dataset of possible future river flows and groundwater levels in the UK and found different outcomes for these two sources of water. Throughout the UK, river flows are likely to be lower in future, with droughts more prolonged and severe. However, whilst these changes are also found in some boreholes, in others, higher levels and less severe drought are indicated for the future. This has implications for the future balance between surface water and groundwater below.
Francesco Marra, Marika Koukoula, Antonio Canale, and Nadav Peleg
Hydrol. Earth Syst. Sci., 28, 375–389, https://doi.org/10.5194/hess-28-375-2024, https://doi.org/10.5194/hess-28-375-2024, 2024
Short summary
Short summary
We present a new physical-based method for estimating extreme sub-hourly precipitation return levels (i.e., intensity–duration–frequency, IDF, curves), which are critical for the estimation of future floods. The proposed model, named TENAX, incorporates temperature as a covariate in a physically consistent manner. It has only a few parameters and can be easily set for any climate station given sub-hourly precipitation and temperature data are available.
Alexander Gelfan, Andrey Panin, Andrey Kalugin, Polina Morozova, Vladimir Semenov, Alexey Sidorchuk, Vadim Ukraintsev, and Konstantin Ushakov
Hydrol. Earth Syst. Sci., 28, 241–259, https://doi.org/10.5194/hess-28-241-2024, https://doi.org/10.5194/hess-28-241-2024, 2024
Short summary
Short summary
Paleogeographical data show that 17–13 ka BP, the Caspian Sea level was 80 m above the current level. There are large disagreements on the genesis of this “Great” Khvalynian transgression of the sea, and we tried to shed light on this issue. Using climate and hydrological models as well as the paleo-reconstructions, we proved that the transgression could be initiated solely by hydroclimatic factors within the deglaciation period in the absence of the glacial meltwater effect.
Joeri B. Reinders and Samuel E. Munoz
Hydrol. Earth Syst. Sci., 28, 217–227, https://doi.org/10.5194/hess-28-217-2024, https://doi.org/10.5194/hess-28-217-2024, 2024
Short summary
Short summary
Flooding presents a major hazard for people and infrastructure along waterways; however, it is challenging to study the likelihood of a flood magnitude occurring regionally due to a lack of long discharge records. We show that hydroclimatic variables like Köppen climate regions and precipitation intensity explain part of the variance in flood frequency distributions and thus reduce the uncertainty of flood probability estimates. This gives water managers a tool to locally improve flood analysis.
Mehrad Rahimpour Asenjan, Francois Brissette, Jean-Luc Martel, and Richard Arsenault
Hydrol. Earth Syst. Sci., 27, 4355–4367, https://doi.org/10.5194/hess-27-4355-2023, https://doi.org/10.5194/hess-27-4355-2023, 2023
Short summary
Short summary
Climate models are central to climate change impact studies. Some models project a future deemed too hot by many. We looked at how including hot models may skew the result of impact studies. Applied to hydrology, this study shows that hot models do not systematically produce hydrological outliers.
Cited articles
Abdalla, S. and Cavaleri, L.: Effect of wind variability and variable air density
on wave modelling, J. Geophys. Res., 107, 17-1–17-17, https://doi.org/10.1029/2000JC000639, 2002.
Abhilash, S., Sahai, A. K., Mohankumar, K., George, J. P., and Das, S.:
Assimilation of doppler weather radar radial velocity and reflectivity
observations in WRF-3DVAR system for short-range forecasting of convective
storms, Pure Appl. Geophys., 169, 2047–2070, https://doi.org/10.1007/s00024-012-0462-z, 2012.
Aligo, E. A., Gallus, W. A., and Segal, M.: On the impact of WRF model vertical
grid resolution on Midwest summer rainfall forecasts, Weather Forecast., 24,
575–594, https://doi.org/10.1175/2008WAF2007101.1, 2009.
Barker, D. M., Huang, W., Guo, Y. R., Bourgeois, A., and Xiao, Q. N.: A
three-dimensional variational data assimilation system for MM5: implementation
and initial results, Mon. Weather Rev., 132, 897–914, https://doi.org/10.1175/1520-0493(2004)132<0897:ATVDAS>2.0.CO;2, 2004.
Bauer, H. S., Schwitalla, T., Wulfmeyer, V., Bakhshall, A., Ehret, U., Neuper,
M., and Caumont, O.: Quantitative precipitation estimation based on
high-resolution numerical weather prediction and data assimilation with WRF – a
performance test, Tellus A, 67, 25047, https://doi.org/10.3402/tellusa.v67.25047, 2015.
Berenguer, M., Surcel, M., Zawadzki, I., Xue, M., and Kong, F.: The diurnal
cycle of precipitation from continental radar mosaics and numerical weather
prediction models. Part II: Intercomparison among numerical models and with
nowcasting, Mon. Weather Rev., 140, 2689–2705, https://doi.org/10.1175/MWR-D-11-00181.1, 2012.
Boussetta, S., Balsamo, G., Beljaars, A., and Kral, T.: Impact of a
satellite-derived Leaf Area Index monthly climatology in a global Numerical
Weather Prediction model, Int. J. Remote Sens., 34, 3520–3542, https://doi.org/10.1080/01431161.2012.716543, 2013.
Carrassi, A., Ghil, M., Trevisan, A., and Uboldi, F.: Data assimilation as a
nonlinear dynamical systems problem: stability and convergence of the
prediction-assimilation system, Chaos, 18, 023112, https://doi.org/10.1063/1.2909862, 2008.
Chambon, P., Zhang, S. Q., Hou, A. Y., Zupanski, M., and Cheung, S.: Assessing
the impact of pre-GPM microwave precipitation observations in the Goddard WRF
ensemble data assimilation system, Q. J. Roy. Meteorol. Soc., 140, 1219–1235,
https://doi.org/10.1002/qj.2215, 2014.
Di, Z., Duan, Q., Gong, W., Wang, C., Gan, Y., Quan, J., Li, J., Miao, C., Ye,
A., and Charles, T.: Assessing WRF model parameter sensitivity: A case study
with 5 day summer precipitation forecasting in the Greater Beijing Area,
Geophys. Res. Lett., 42, 579–587, https://doi.org/10.1002/2014GL061623, 2015.
Done, J., Davis, C. A., and Weisman, M.: The next generation of NWP: explicit
forecasts of convection using the weather research and forecasting (WRF) model,
Atmos. Sci. Lett., 5, 110–117, https://doi.org/10.1002/asl.72, 2004.
Dong, J. and Xue, M.: Assimilation of radial velocity and reflectivity data
from coastal WSR-88D radars using an ensemble Kalman filter for the analysis
and forecast of landfalling hurricane Ike (2008), Q. J. Roy. Meteorol. Soc.,
139, 467–487, https://doi.org/10.1002/qj.1970, 2013.
Dudhia, J.: Numerical study of convection observed during the winter monsoon
experiment using a mesoscale two-dimensional model, J. Atmos. Sci., 46,
3077–3107, https://doi.org/10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2, 1989.
Efstathiou, G. A., Zoumakis, N. M., Melas, D., Lolis, C. J., and Kassomenos,
P.: Sensitivity of WRF to boundary layer parameterizations in simulating a
heavy rainfall event using different microphysical schemes, Effect on large-scale
processes, Atmos. Res., 132, 125–143, https://doi.org/10.1016/j.atmosres.2013.05.004, 2013.
Fernández-González, S., Valero, F., Sánchez, J. L., Gascón, E.,
López, L., García-Ortega, E., and Merino, A.: Numerical simulations of
snowfall events: Sensitivity analysis of physical parameterizations, J. Geophys.
Res.-Atmos., 120, 10130–10148, https://doi.org/10.1002/2015JD023793, 2015.
Fierro, A. O., Mansell, E. R., Macgorman, D. R., and Ziegler, C. L.: The
implementation of an explicit charging and discharge lightning scheme within
the WRF-ARW model: benchmark simulations of a continental squall line, a
tropical cyclone, and a winter storm, Mon. Weather Rev., 141, 2390–2415,
https://doi.org/10.1175/MWR-D-12-00278.1, 2013.
Gao, J. D., Xue, M., Brewster, K. A., and Droegemeier, K.: A three-dimensional
variational data analysis method with recursive filter for Doppler radars, J.
Atmos. Ocean. Tech., 21, 457–469, https://doi.org/10.1175/1520-0426(2004)021<0457:ATVDAM>2.0.CO;2, 2004.
Gascón, E., Laviola, S., Merino, A., and Miglietta, M. M.: Analysis of a
localized flash-flood event over the central Mediterranean, Atmos. Res., 182,
256–268, https://doi.org/10.1016/j.atmosres.2016.08.007, 2016.
Georgakakos, K. P.: Covariance propagation and updating in the context of
real-time radar data assimilation by quantitative precipitation forecast models,
J. Hydrol., 239, 115–129, https://doi.org/10.1016/S0022-1694(00)00355-3, 2000.
Givati, A., Lynn, B., Liu, Y., and Rimmer, A.: Using the WRF model in an
operational streamflow forecast system for the Jordan River, J. Appl. Meteorol.
Clim., 51, 285–299, https://doi.org/10.1175/JAMC-D-11-082.1, 2012.
Guo, C., Xiao, H., Yang, H., and Tang, Q.: Observation and modeling analyses
of the macro-and microphysical characteristics of a heavy rain storm in Beijing,
Atmos. Res., 156, 125–141, https://doi.org/10.1016/j.atmosres.2015.01.007, 2015.
Guo, X., Fu, D., Guo, X., and Zhang, C.: A case study of aerosol impacts on
summer convective clouds and precipitation over northern China, Atmos. Res.,
142, 142–157, https://doi.org/10.1016/j.atmosres.2013.10.006, 2014.
Ha, J. H. and Lee, D. K.: Effect of length scale tuning of bachground error in
WRF-3DVar system on assimilation of high-resolution surface data for heavy
rainfall simulation, Adv. Atmos. Sci., 29, 1142–1158, https://doi.org/10.1007/s00376-012-1183-z, 2012.
Ha, J. H., Lim, G. H., and Choi, S. J.: Assimilation of GPS radio occultation
refractivity data with WRF 3DVAR and its impact on the prediction of a heavy
rainfall event, J. Appl. Meteorol. Clim., 53, 1381–1398, https://doi.org/10.1175/JAMC-D-13-0224.1, 2014.
Hamill, T. M.: Performance of Operational model precipitation forecast guidance
during the 2013 Colorado front-range floods, Mon. Weather Rev., 142, 2609–2618,
https://doi.org/10.1175/MWR-D-14-00007.1, 2014.
Hunter, S. M.: WSR-88D radar rainfall estimation: Capabilities, limitations
and potential improvements, Natl. Weather Dig., 20, 26–38, 1996.
Ide, K., Courtier, P., Ghil, M., and Lorenc, A. C.: Unified Notation for data
assimilation: Operational, sequential and variational, J. Meteorol. Soc. Jpn.,
75, 181–189, 1997.
Janjić, Z. I.: The step-mountain eta coordinate model: further developments
of the convection, viscous sublayer, and turbulence closure schemes, Mon.
Weather Rev., 122, 927–945, https://doi.org/10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2, 1994.
Jr, J. H. R. and Johnson, R. H.: On the cumulus diurnal cycle over the tropical
warm pool, J. Adv. Model Earth Syst., 8, 669–690, https://doi.org/10.1002/2015MS000610, 2016.
Kain, J. S.: The Kain-Fritsch convective parameterization: an update, J. Appl.
Meteorol., 43, 170–181, https://doi.org/10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2, 2004.
Kim, J. H., Shin, D. B., and Kummerow, C.: Impacts of a priori databases using
six WRF microphysics schemes on passive microwave rainfall retrievals, J. Atmos.
Ocean. Tech., 30, 2367–2381, https://doi.org/10.1175/JTECH-D-12-00261.1, 2013.
Kryza, M., Werner, M., Wałszek, K., and Dore, A. J.: Application and evaluation
of the WRF model for high-resolution forecasting of rainfall – a case study of
SW Poland, Meteorol. Z., 22, 595–601, https://doi.org/10.1127/0941-2948/2013/0444, 2013.
Li, Y., Wang, X., and Xue, M.: Assimilation of radar radial velocity data with
the WRF hybrid ensemble – 3DVAR system for the prediction of Hurricane Ike (2008),
Mon. Weather Rev., 140, 3507–3524, https://doi.org/10.1175/MWR-D-12-00043.1, 2012.
Lin, H. H., Lin, P. L., Xiao, Q., and Kuo, Y. H.: Effect of Doppler radial
velocity data assimilation on the simulation of a typhoon approaching Taiwan:
A case study of Typhoon Aere (2004), Terr. Atmos. Ocean. Sci., 22, 325–345,
https://doi.org/10.3319/TAO.2010.10.08.01(A), 2011.
Liu, J. and Han, D.: On selection of the optimal data time interval for real-time
hydrological forecasting, Hydrol. Earth Syst. Sci., 17, 3639–3659,
https://doi.org/10.5194/hess-17-3639-2013, 2013.
Liu, J., Bray, M., and Han, D.: Sensitivity of the Weather Research and
Forecasting (WRF) model to downscaling ratios and storm types in rainfall
simulation, Hydrol. Process., 26, 3012–3031, https://doi.org/10.1002/hyp.8247, 2012.
Liu, J., Bray, M., and Han, D.: A study on WRF radar data assimilation for
hydrological rainfall precipitation, Hydrol. Earth Syst. Sci., 17, 3095–3110,
https://doi.org/10.5194/hess-17-3095-2013, 2013a.
Liu, J., Bray, M., and Han, D.: Exploring the effect of data assimilation by
WRF-3DVar for numerical rainfall prediction with different types of storm
events, Hydrol. Process., 27, 3627–3640, https://doi.org/10.1002/hyp.9488, 2013b.
Liu, J., Wang, J., Pan, S., Tang, K., Li, C., and Han, D.: A real-time flood
forecasting system with dual updating of the NWP rainfall and the river flow,
Nat. Hazards., 77, 1161–1182, https://doi.org/10.1007/s11069-015-1643-8, 2015.
Maiello, I., Ferretti, R., Gentile, S., Montopoli, M., Picciotti, E., Marzano,
F. S., and Faccani, C.: Impact of radar data assimilation for the simulation
of a heavy rainfall case in central Italy using WRF–3DVAR, Atmos. Meas. Tech.,
7, 2919–2935, https://doi.org/10.5194/amt-7-2919-2014, 2014.
Meng, Z. and Zhang, F.: Tests of an ensemble Kalman filter for mesoscale and
regional-scale data assimilation, Part IV: Comparison with 3DVAR in a month-long
experiment, Mon. Weather Rev., 136, 3671–3682, https://doi.org/10.1175/2007MWR2106.1, 2008.
Miao, S., Chen, F., and Li, Q.: Impacts of urban processes and urbanization on
summer precipitation: A case study of heavy rainfall in Beijing on 1 August 2006,
J. Appl. Meteorol. Clim., 50, 806–825, https://doi.org/10.1175/2007MWR2106.1, 2011.
Mohanty, U. C., Routray, A., Osuri, K. K., and Prasad, S. K.: A study on
simulation of heavy rainfall events over Indian region with ARW-3DVAR modeling
system, Pure Appl. Geophys., 169, 381–399, https://doi.org/10.1007/s00024-011-0376-1, 2012.
Montmerle, T. and Faccani, C.: Mesoscale assimilation of radial velocities from
Doppler radars in a preoperational framework, Mon. Weather Rev., 137, 1939–1953,
https://doi.org/10.1175/2008MWR2725.1, 2010.
Pan, X., Tian, X., Li, X., Xie, Z., Shao, A., and Lu, C.: Assimilating Doppler
radar radial velocity and reflectivity observations in the weather research and
forecasting model by a proper orthogonal-decomposition-based ensemble,
three-dimensional variational assimilation method, J. Geophys. Res.-Atmos.,
117, D17113, https://doi.org/10.1029/2012JD017684, 2012.
Pan, X., Li, X., Cheng, G., and Hong, Y.: Effects of 4D-Var data assimilation
using remote sensing precipitation products in a WRF model over the complex
terrain of an arid region river basin, Remote Sensing, 9, 963, https://doi.org/10.3390/rs9090963, 2017.
Pu, Z., Li, X., and Sun, J.: Impact of airborne Doppler radar data assimilation
on the numerical simulation of intensity changes of Hurricane Dennis near a
landfall, J. Atmos. Sci., 66, 3351–3365, https://doi.org/10.1175/2009JAS3121.1, 2009.
Qie, X., Zhu, R., Yuan, T., Wu, X., Li, W., and Liu, D.: Application of
total-lightning data assimilation in a mesoscale convective system based on the
WRF model, Atmos. Res., 145–146, 255–266, https://doi.org/10.1016/j.atmosres.2014.04.012, 2014.
Rodwell, M. J., Richardson, D. S., Hewson, T. D., and Haiden, T.: A new equitable
score suitable for verifying precipitation in numerical weather prediction, Q.
J. Roy. Meteorol. Soc., 136, 1344–1363, https://doi.org/10.1002/qj.65, 2010.
Rossa, A. M., Guerra, F. L. D., Borga, M., Zanon, F., Settin, T., and Leuenberger,
D.: Radar-driven high-resolution hydro-meteorological forecasts of the 26 September 2007
Venice flash flood, J. Hydrol., 394, 230–244, https://doi.org/10.1016/j.jhydrol.2010.08.035, 2010.
Routray, A., Mohanty, U. C., Niyogi, D., Rizvi, S. R. H., and Osuri, K. K.:
Simulation of heavy rainfall events over Indian monsoon region using WRF-3DVAR
data assimilation system, Meteorol. Atmos. Phys., 106, 107–125, https://doi.org/10.1007/s00703-009-0054-3, 2010.
Routray, A., Osuri, K. K., and Kulkarni, M. A.: A comparative study on
performance of analysis nudging and 3DVAR in simulation of a heavy rainfall
event using WRF modeling system, Isrn. Meteorol., 2012, 1191–1213, https://doi.org/10.5402/2012/523942, 2012.
Sang, Y. F., Wang, Z., and Liu, C.: What factors are responsible for the Beijing
storm, Nat. Hazards, 65, 2399–2400, https://doi.org/10.1007/s11069-012-0426-8, 2013.
Schraff, C., Reich, H., Rhodin, A., Schomburg, A., Stephan, K., Perianez, A.,
and Potthast, R.: Kilometre-scale ensemble data assimilation for the COSMO
model (KENDA), Q. J. Roy. Meteorol. Soc., 142, 1453–1472, https://doi.org/10.1002/qj.2748, 2016.
Shih, D. S., Chen, C. H., and Yeh, G. T.: Improving our understanding of flood
forecasting using earlier hydro-meteorological intelligence, J. Hydrol., 512,
470–481, https://doi.org/10.1016/j.jhydrol.2014.02.059, 2014.
Shrestha, D. L., Robertson, D. E., Wang, Q. J., Pagano, T. C., and Hapuarachchi,
H. A. P.: Evaluation of numerical weather prediction model precipitation
forecasts for short-term streamflow forecasting purpose, Hydrol. Earth. Syst.
Sci., 17, 1913–1931, https://doi.org/10.5194/hess-17-1913-2013, 2013.
Skamaraock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Duda,
M. G., Huang, X. Y., Wang, W., and Powers, J. G.: A description of the advanced
research WRF Version 3, NCAR technical note, available at: http://www.ncar.ucar.edu,
last access: 6 January 2008.
Sokol, Z. and Pešice, P.: Comparing nowcastings of three severe convective
events by statistical and NWP models, Atmos. Res., 93, 397–407, https://doi.org/10.1016/j.atmosres.2008.09.016, 2009.
Stephan, K., Klink, S., and Schraff, C.: Assimilation of radar-derived rain
rates into the convective-scale model COSMO-DE at DWD, Q. J. Roy. Meteorol. Soc.,
134, 1315–1326, https://doi.org/10.1002/qj.269, 2010.
Sugimoto, S., Crook, N. A., Sun, J., Xiao, Q., and Barker, D. M.: An examination
of WRF 3DVAR radar data assimilation on its capability in retrieving unobserved
variables and forecasting precipitation through observing system simulation
experiments, Mon. Weather Rev., 137, 4011–4029, https://doi.org/10.1175/2009MWR2839.1, 2009.
Sun, J.: Convective-scale assimilation of radar data: progress and challenges,
Q. J. Roy. Meteorol. Soc., 131, 3439–3463, https://doi.org/10.1256/qj.05.149, 2005.
Sun, J. and Crook, N. A.: Dynamical and microphysical retrieval from Doppler
radar observations using a cloud model and its adjoint. Part I: Model development
and simulated data experiments, J. Atmos. Sci., 54, 1642–1661, https://doi.org/10.1175/1520-0469(1997)054<1642:DAMRFD>2.0.CO;2, 1997.
Sun, J. and Crook, N. A.: Dynamical and microphysical retrieval from Doppler
radar observations using a cloud model and its adjoint. Part II: Retrieval
experiments of an observed Florida convective storm, J. Atmos. Sci., 55,
835–852, https://doi.org/10.1175/1520-0469(1998)055<0835:DAMRFD>2.0.CO;2, 1998.
Sun, J., Trier, S. B., Xiao, Q., Weisman, M. L., Wang, H., Ying, Z., Xu, M.,
and Zhang, Y.: Sensitivity of 0-12-h warm-season precipitation forecasts over
the central United States to model initialization, Weather Forecast., 27,
832–855, https://doi.org/10.1175/WAF-D-11-00075.1, 2012.
Sun, J., Wang, H., Tong, W., Zhang, Y., Lin, C. Y., and Xu, D.: Comparison of
the impacts of momentum control variables on high-resolution variational data
assimilation and precipitation forecasting, Mon. Weather Rev., 144, 149–169,
https://doi.org/10.1175/MWR-D-14-00205.1, 2016.
Tian, J., Liu, J., Wang, J., Li, C., Yu, F., and Chu, Z.: A spatio-temporal
evaluation of the WRF physical parameterisations for numerical rainfall
simulation in semi-humid and semi-arid catchments of Northern China, Atmos.
Res., 191, 141–155, https://doi.org/10.1016/j.atmosres.2017.03.012, 2017a.
Tian, J., Liu, J., Yan, D., Li, C., Chu, Z., and Yu, F.: An assimilation test
of Doppler radar reflectivity and radial velocity from different height layers
in improving the WRF rainfall forecasts, Atmos. Res., 198, 132–144,
https://doi.org/10.1016/j.atmosres.2017.08.004, 2017b.
Tian, J., Liu, J., Yan, D., Li, C., and Yu, F.: Numerical rainfall simulation
with different spatial and temporal evenness by using a WRF multiphysics ensemble,
Nat. Hazards Earth Syst. Sci., 17, 563–579, https://doi.org/10.5194/nhess-17-563-2017, 2017c.
Tong, M. and Xue, M.: Ensemble Kalman filter assimilation of Doppler radar
data with a compressible nonhydrostatic model: OSS Experiments, Mon. Weather
Rev., 133, 1789–1807, https://doi.org/10.1175/MWR2898.1, 2005.
Tu, C. C., Chen, Y. L., Chen, S. Y., Kuo, Y. H., and Lin, P. L.: Impacts of
including rain-evaporative cooling in the initial conditions on the prediction
of a coastal heavy rainfall event during TiMREX, Mon. Weather Rev., 145,
253–277, https://doi.org/10.1175/MWR-D-16-0224.1, 2017.
Wang, H., Sun, J., Fan, S., and Huang, X.: Indirect assimilation of radar
reflectivity with WRF 3D-Var and its impact on prediction of four summertime
convective events, J. Appl. Meteorol. Clim., 52, 889–902, https://doi.org/10.1175/JAMC-D-12-0120.1, 2013.
Xiao, Q. and Sun, J.: Multiple-radar data assimilation and short-range
quantitative precipitation forecasting of a squall line observed during,
IHOP_2002, Mon. Weather Rev., 135, 3381–3404, https://doi.org/10.1175/MWR3471.1, 2007.
Xiao, Q., Kuo, Y. H., Sun, J., Lee, W. C., Lim, E., Guo, Y. R., and Barker, D.
M.: Assimilation of Doppler radar observations with a regional 3DVAR System:
Impact of Doppler velocities on forecasts of a heavy rainfall case, J. Appl.
Meteorol., 44, 768–788, https://doi.org/10.1175/JAM2248.1, 2005.
Yang, B., Zhang, Y., Qian, Y., Huang, A., and Yan, H.: Calibration of a
convective parameterization scheme in the WRF model and its impact on the
simulation of East Asian summer monsoon precipitation, Clim. Dynam., 44,
1661–1684, https://doi.org/10.1007/s00382-014-2118-4, 2015.
Yucel, I., Onen, A., Yilmaz, K. K., and Gochis, D. J.: Calibration and
evaluation of a flood forecasting system: Utility of numerical weather
prediction model, data assimilation and satellite-based rainfall, J. Hydrol.,
523, 49–66, https://doi.org/10.1016/j.jhydrol.2015.01.042, 2015.
Zhang, L., Pu, Z., Lee, W. C., and Zhao, Q.: The influence of airborne Doppler
radar data quality on numerical simulations of a tropical cyclone, Weather
Forecast., 27, 231–239, https://doi.org/10.1175/WAF-D-11-00028.1, 2012.
Zhong, L., Mu, R., Zhang, D., Zhao, P., Zhang, Z., and Wang, N.: An observational
analysis of warm-sector rainfall characteristics associated with the 21 July 2012
Beijing extreme rainfall event, J. Geophys. Res., 120, 3274–3291, https://doi.org/10.1002/2014JD022686, 2015.
Short summary
Both radar reflectivity and GTS data are good choices for assimilation in improving high-resolution rainfall of the NWP systems, which always fails in providing satisfactory rainfall products for hydrological use. Simultaneously assimilating GTS and radar data always performs better than assimilating radar data alone. The assimilation efficiency of the GTS data is higher than both radar reflectivity and radial velocity considering the number of data assimilated and its effect.
Both radar reflectivity and GTS data are good choices for assimilation in improving...
