scholarly journals Development of high-resolution 72 h precipitation and hillslope flood maps over a tropical transboundary region by physically based numerical atmospheric–hydrologic modeling

2020 ◽  
Vol 11 (S1) ◽  
pp. 387-406 ◽  
Author(s):  
T. Trinh ◽  
C. Ho ◽  
N. Do ◽  
A. Ercan ◽  
M. L. Kavvas
Keyword(s):  
High Resolution ◽  
Water Resource Management ◽  
Wrf Model ◽  
Heavy Precipitation ◽  
Reanalysis Data ◽  
Observation Data ◽  
Extreme Flood ◽  
Hydrologic Data ◽  
Flood Maps

Abstract Long-term, high spatial and temporal resolution atmospheric and hydrologic data are crucial for water resource management. However, reliable high-quality precipitation and hydrologic data are not available in various regions around the world. This is, in particular, the case in transboundary regions, which have no formal data sharing agreement among countries. This study introduces an approach to construct long-term high-resolution extreme 72 h precipitation and hillslope flood maps over a tropical transboundary region by the coupled physical hydroclimate WEHY-WRF model. For the case study, Da and Thao River watersheds (D-TRW), within Vietnam and China, were selected. The WEHY-WRF model was set up over the target region based on ERA-20C reanalysis data and was calibrated based on existing ground observation data. After successfully configuring, WEHY-WRF is able to produce hourly atmospheric and hydrologic conditions at fine resolution over the target watersheds during 1900–2010. From the modeled 72 h precipitation and flood events, it can be seen that the main precipitation mechanism of DRW and TRW are both the summer monsoon and tropical cyclone. In addition, it can be concluded that heavy precipitation may not be the only reason to create an extreme flood event. The effects of topography, soil, and land use/cover also need to be considered in such nonlinear atmospheric and hydrologic processes. Last but not least, the long-term high-resolution extreme 72 h precipitation and hillslope flood maps over a tropical transboundary region, D-TRW, were constructed based on 111 largest annual historical events during 1900–2010.

scholarly journals Radar-based characterisation of heavy precipitation in the eastern Mediterranean and its representation in a convection-permitting model

2020 ◽  
Vol 24 (3) ◽  
pp. 1227-1249 ◽  
Author(s):  
Moshe Armon ◽  
Francesco Marra ◽  
Yehouda Enzel ◽  
Dorita Rostkier-Edelstein ◽  
Efrat Morin
Keyword(s):  
High Resolution ◽  
Eastern Mediterranean ◽  
Wrf Model ◽  
Heavy Precipitation ◽  
Spatial Location ◽  
Radar Data ◽  
Weather Research And Forecasting ◽  
Model Simulations ◽  
Rain Gauges ◽  
Rainfall Patterns

Abstract. Heavy precipitation events (HPEs) can lead to natural hazards (e.g. floods and debris flows) and contribute to water resources. Spatiotemporal rainfall patterns govern the hydrological, geomorphological, and societal effects of HPEs. Thus, a correct characterisation and prediction of rainfall patterns is crucial for coping with these events. Information from rain gauges is generally limited due to the sparseness of the networks, especially in the presence of sharp climatic gradients. Forecasting HPEs depends on the ability of weather models to generate credible rainfall patterns. This paper characterises rainfall patterns during HPEs based on high-resolution weather radar data and evaluates the performance of a high-resolution, convection-permitting Weather Research and Forecasting (WRF) model in simulating these patterns. We identified 41 HPEs in the eastern Mediterranean from a 24-year radar record using local thresholds based on quantiles for different durations, classified these events into two synoptic systems, and ran model simulations for them. For most durations, HPEs near the coastline were characterised by the highest rain intensities; however, for short durations, the highest rain intensities were found for the inland desert. During the rainy season, the rain field's centre of mass progresses from the sea inland. Rainfall during HPEs is highly localised in both space (less than a 10 km decorrelation distance) and time (less than 5 min). WRF model simulations were accurate in generating the structure and location of the rain fields in 39 out of 41 HPEs. However, they showed a positive bias relative to the radar estimates and exhibited errors in the spatial location of the heaviest precipitation. Our results indicate that convection-permitting model outputs can provide reliable climatological analyses of heavy precipitation patterns; conversely, flood forecasting requires the use of ensemble simulations to overcome the spatial location errors.

scholarly journals BAYWRF: a high-resolution present-day climatological atmospheric dataset for Bavaria

2020 ◽  
Vol 12 (4) ◽  
pp. 3097-3112
Author(s):  
Emily Collier ◽  
Thomas Mölg
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Large Scale ◽  
Wrf Model ◽  
Atmospheric Model ◽  
Climate Impact ◽  
Reanalysis Data ◽  
Near Surface ◽  
Local Climate ◽  
The Impact

Abstract. Climate impact assessments require information about climate change at regional and ideally also local scales. In dendroecological studies, this information has traditionally been obtained using statistical methods, which preclude the linkage of local climate changes to large-scale drivers in a process-based way. As part of recent efforts to investigate the impact of climate change on forest ecosystems in Bavaria, Germany, we developed a high-resolution atmospheric modelling dataset, BAYWRF, for this region over the thirty-year period of September 1987 to August 2018. The atmospheric model employed in this study, the Weather Research and Forecasting (WRF) model, was configured with two nested domains of 7.5 and 1.5 km grid spacing centred over Bavaria and forced at the outer lateral boundaries by ERA5 reanalysis data. Using an extensive network of observational data, we evaluate (i) the impact of using grid analysis nudging for a single-year simulation of the period of September 2017 to August 2018 and (ii) the full BAYWRF dataset generated using nudging. The evaluation shows that the model represents variability in near-surface meteorological conditions generally well, although there are both seasonal and spatial biases in the dataset that interested users should take into account. BAYWRF provides a unique and valuable tool for investigating climate change in Bavaria with high interdisciplinary relevance. Data from the finest-resolution WRF domain are available for download at daily temporal resolution from a public repository at the Open Science Framework (Collier, 2020; https://doi.org/10.17605/OSF.IO/AQ58B).

Radar-based characterization of heavy precipitation in the eastern Mediterranean and its representation in a convection-permitting model

2020 ◽  
Author(s):  
Efrat Morin ◽  
Moshe Armon ◽  
Francesco Marra ◽  
Yehouda Enzel ◽  
Dorita Rostkier-Edelstein
Keyword(s):  
High Resolution ◽  
Eastern Mediterranean ◽  
Center Of Mass ◽  
Wrf Model ◽  
Heavy Precipitation ◽  
Spatial Location ◽  
Radar Data ◽  
Model Simulations ◽  
Rain Gauges ◽  
Rainfall Patterns

<p>Heavy precipitation events (HPEs) can lead to natural hazards (floods, debris flows) and contribute to water resources. Spatiotemporal rainfall patterns govern the hydrological, geomorphological and societal effects of HPEs. Thus, a correct characterization and prediction of rainfall patterns is crucial for coping with these events. However, information from rain gauges suitable for these goals is generally limited due to the sparseness of the networks, especially in the presence of sharp climatic gradients and small precipitating systems. Forecasting HPEs depends on the ability of weather models to generate credible rainfall patterns. In this study we characterize rainfall patterns during HPEs based on high-resolution weather radar data and evaluate the performance of a high-resolution (1 km<sup>2</sup>), convection-permitting Weather Research and Forecasting (WRF) model in simulating these patterns. We identified 41 HPEs in the eastern Mediterranean from a 24-year long radar record using local thresholds based on quantiles for different durations, classified these events into two synoptic systems, and ran model simulations for them. For most durations, HPEs near the coastline were characterized by the highest rain intensities; however, for short storm durations, the highest rain intensities were characterized for the inland desert. During the rainy season, center of mass of the rain field progresses from the sea inland. Rainfall during HPEs is highly localized in both space (<10 km decorrelation distance) and time (<5 min). WRF model simulations accurately generate the structure and location of the rain fields in 39 out of 41 HPEs. However, they showed a positive bias relative to the radar estimates and exhibited errors in the spatial location of the heaviest precipitation. Our results indicate that convection-permitting model outputs can provide reliable climatological analyses of heavy precipitation patterns; conversely, flood forecasting requires the use of ensemble simulations to overcome the spatial location errors.</p>

Sensitivity of Convective Cell Dynamics and Microphysics to Model Resolution for the OWLeS IOP2b Lake-Effect Snowband

2020 ◽  
Vol 148 (8) ◽  
pp. 3305-3328 ◽  
Author(s):  
Anders A. Jensen ◽  
Philip T. Bergmaier ◽  
Bart Geerts ◽  
Hugh Morrison ◽  
Leah S. Campbell
Keyword(s):  
High Resolution ◽  
Wrf Model ◽  
Heavy Precipitation ◽  
Convective Cell ◽  
Maximum Diameter ◽  
Grid Spacing ◽  
Particle Properties ◽  
Lake Effect ◽  
Aircraft Observations ◽  
Horizontal Grid

Abstract The OWLeS IOP2b lake-effect case is simulated using the Weather Research and Forecasting (WRF) Model with a horizontal grid spacing of 148 m (WRF-LES mode). The dynamics and microphysics of the simulated high-resolution snowband and a coarser-resolution band from the parent nest (1.33-km horizontal grid spacing) are compared to radar and aircraft observations. The Ice Spheroids Habit Model with Aspect-ratio Evolution (ISHMAEL) microphysics is used, which predicts the evolution of ice particle properties including shape, maximum diameter, density, and fall speed. The microphysical changes within the band that occur when going from 1.33-km to 148-m grid spacing are explored. Improved representation of the dynamics at higher resolution leads to a better representation of the microphysics of the snowband compared to radar and aircraft observations. Stronger updrafts in the high-resolution grid produce higher ice number concentrations and produce ice particles that are more heavily rimed and thus more spherical, smaller (in terms of mean maximum diameter), and faster falling. These changes to the ice particle properties in the high-resolution grid limit the production of aggregates and improve reflectivity compared to observations. Graupel, observed in the band at the surface, is simulated in the strongest convective updrafts, but only at the higher resolution. Ultimately, the duration of heavy precipitation just onshore from the collapse of convection is better predicted in the high-resolution domain compared to surface and radar observations.

Assessment of atmospheric conditions over the Hong Thai Binh river watershed by means of dynamically downscaled ERA-20C reanalysis data

2018 ◽  
Vol 11 (2) ◽  
pp. 540-555 ◽  
Author(s):  
C. Ho ◽  
A. Nguyen ◽  
A. Ercan ◽  
M. L. Kavvas ◽  
V. Nguyen ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Wrf Model ◽  
Reanalysis Data ◽  
Observation Data ◽  
Human Society ◽  
Atmospheric Conditions ◽  
Study Region ◽  
River Watershed ◽  
Environmentally Sustainable ◽  
Atmospheric Data

Abstract Long-term, high spatial and temporal resolution of atmospheric data is crucial for the purpose of reducing the effects of hydro-meteorological risks on human society in an economically and environmentally sustainable manner. However, such information usually is limited in transboundary regions due to different governmental policies, and to conflicts in the sharing of data. In this study, high spatial and temporal resolution atmospheric data were reconstructed by means of the Weather Research and Forecasting Model-WRF with input provided from the global atmospheric reanalysis of the 20th century (ERA-20C) over the Hong-Thai Binh River watershed (H-TBRW). The WRF model was implemented over the physical boundaries of the study region based on ERA-20C reanalysis data and was configured based on existing ground observation data in Vietnam's territories, and the global Aphrodite precipitation data. With the validated WRF model for H-TBRW, the reconstructed atmospheric data were first reconstructed for 1950–2010, and then were evaluated by time series and spatial analysis methods. The results of this study suggest no significant trend in the annual accumulated precipitation depth, while there were upward trends in annual temperature at both the point and watershed scale. Furthermore, the results confirm that topographic conditions have significant effects on the climatic system such as on precipitation and temperature.

scholarly journals APHRODITE: Constructing a Long-Term Daily Gridded Precipitation Dataset for Asia Based on a Dense Network of Rain Gauges

2012 ◽  
Vol 93 (9) ◽  
pp. 1401-1415 ◽  
Author(s):  
Akiyo Yatagai ◽  
Kenji Kamiguchi ◽  
Osamu Arakawa ◽  
Atsushi Hamada ◽  
Natsuko Yasutomi ◽  
...  
Keyword(s):  
High Resolution ◽  
Water Resources ◽  
Middle East ◽  
Northern Eurasia ◽  
Observation Data ◽  
Telecommunication System ◽  
Mountainous Regions ◽  
Continental Scale ◽  
Global Telecommunication System

A daily gridded precipitation dataset covering a period of more than 57 yr was created by collecting and analyzing rain gauge observation data across Asia through the activities of the Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) project. APHRODITE's daily gridded precipitation is presently the only long-term, continental-scale, high-resolution daily product. The product is based on data collected at 5,000–12,000 stations, which represent 2.3–4.5 times the data made available through the Global Telecommunication System network and is used for most daily gridded precipitation products. Hence, the APHRODITE project has substantially improved the depiction of the areal distribution and variability of precipitation around the Himalayas, Southeast Asia, and mountainous regions of the Middle East. The APHRODITE project now contributes to studies such as the determination of Asian monsoon precipitation change, evaluation of water resources, verification of high-resolution model simulations and satellite precipitation estimates, and improvement of precipitation forecasts. The APHRODITE project carries out outreach activities with Asian countries, and communicates with national institutions and world data centers. We have released open-access APHRO_V1101 datasets for monsoon Asia, the Middle East, and northern Eurasia (at 0.5° × 0.5° and 0.25° × 0.25° resolution) and the APHRO_JP_V1005 dataset for Japan (at 0.05° × 0.05° resolution; see www.chikyu.ac.jp/precip/ and http://aphrodite.suiri.tsukuba.ac.jp/). We welcome cooperation and feedback from users.

scholarly journals Characterising patterns of heavy precipitation events in the eastern Mediterranean using a weather radar and convection-permitting WRF simulations

2019 ◽  
Author(s):  
Moshe Armon ◽  
Francesco Marra ◽  
Yehouda Enzel ◽  
Dorita Rostkier-Edelstein ◽  
Efrat Morin
Keyword(s):  
High Resolution ◽  
Eastern Mediterranean ◽  
Wrf Model ◽  
Weather Radar ◽  
Heavy Precipitation ◽  
Radar Data ◽  
Weather Research And Forecasting ◽  
Rain Gauges ◽  
Rainfall Patterns ◽  
Precipitation Events

Abstract. Heavy precipitation events (HPEs) can lead to natural hazards (floods, debris flows) and contribute to water resources. Rainfall patterns govern HPEs effects. Thus, a correct characterisation and prediction of rainfall patterns is crucial for coping with HPEs. Information from rain gauges is generally limited due to the sparseness of the networks, especially in presence of sharp climatic gradients. Forecasting HPEs depends on the ability of weather models to generate credible rainfall patterns. This paper characterises rainfall patterns during HPEs based on high-resolution weather radar data and evaluates the performance of a high-resolution, convection-permitting, Weather Research and Forecasting (WRF) model in simulating these patterns. We identified 41 HPEs in the eastern Mediterranean from a 24-year radar record using local thresholds based on quantiles for different durations, and we ran model simulations of these events. For most durations, HPEs near the coastline are characterised by the highest rain intensities, however, for short durations, the highest rain intensities characterise the inland desert. During the rainy season, the centre-of-mass of the rain field progresses from the sea inland. Rainfall during HPEs is highly localised both in space (

Origins of Heavy Precipitation Biases in the TRMM PR and TMI Products Assessed with CloudSat and Reanalysis Data

2019 ◽  
Vol 58 (1) ◽  
pp. 37-54 ◽  
Author(s):  
Andung Bayu Sekaranom ◽  
Hirohiko Masunaga
Keyword(s):  
Heavy Rainfall ◽  
Tropical Rainfall Measuring Mission ◽  
Heavy Precipitation ◽  
Reanalysis Data ◽  
Observation Data ◽  
Tropical Ocean ◽  
Rainfall Events ◽  
Convective Systems ◽  
Microwave Imager ◽  
Heavy Rainfall Events

AbstractThis study aims to characterize the background physical processes in the development of those heavy precipitation clouds that contribute to the Tropical Rainfall Measuring Mission (TRMM) active and passive sensor differences. The combined global observation data from TRMM, CloudSat, and European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) from 2006 to 2014 were utilized to address this issue. Heavy rainfall events were extracted from the top 10% of the rain events from the Precipitation Radar (PR) and TRMM Microwave Imager (TMI) rain-rate climatology. Composite analyses of CloudSat and ERA-Interim were conducted to identify the detailed cloud structures and the background environmental conditions. Over tropical land, TMI tends to preferentially detect deep isolated precipitation clouds for relatively drier and unstable environments, while PR identifies more organized systems. Over the tropical ocean, TMI identifies heavy rainfall events with notable convective organization and clear regional gradients between the western and eastern Pacific Ocean, while PR fails to capture the eastward shallowing of convective systems. The PR–TMI differences for the moist and stable environments are reversed over tropical land.

Developing configuration of WRF model for long-term high-resolution wind wave hindcast over the North Atlantic with WAVEWATCH III

2018 ◽  
Vol 68 (11) ◽  
pp. 1593-1604 ◽  
Author(s):  
Margarita Markina ◽  
Alexander Gavrikov ◽  
Sergey Gulev ◽  
Bernard Barnier
Keyword(s):  
High Resolution ◽  
North Atlantic ◽  
Wind Wave ◽  
Wrf Model ◽  
Wavewatch Iii ◽  
Wave Hindcast ◽  
The North ◽  
The North Atlantic

scholarly journals Long-term Variances of Heavy Precipitation across Central Europe using a Large Ensemble of Regional Climate Model Simulations

2019 ◽  
Author(s):  
Florian Ehmele ◽  
Lisa-Ann Kautz ◽  
Hendrik Feldmann ◽  
Joaquim G. Pinto
Keyword(s):  
Regional Climate Model ◽  
Central Europe ◽  
Climate Model ◽  
Extreme Values ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
Data Sets ◽  
Observation Data ◽  
Large Ensemble

Abstract. Widespread flooding events are among the major natural hazards in Central Europe. Such events are usually related to intensive, long-lasting precipitation. Despite some prominent floods during the last three decades (e.g. 1997, 1999, 2002, and 2013), extreme floods are rare and associated with estimated long return periods of more than 100 years. To assess the associated risks of such extreme events, reliable statistics of precipitation and discharge are required. Comprehensive observations, however, are mainly available for the last 50–60 years or less. This shortcoming can be reduced using stochastic data sets. One possibility towards this aim is to consider climate model data or extended reanalyses. This study presents and discusses a validation of different century-long data sets, a large ensemble of decadal hindcasts, and also projections for the upcoming decade. Global reanalysis for the 20th century with a horizontal resolution of more than 100 km have been dynamically downscaled with a regional climate model (COSMO-CLM) towards a higher resolution of 25 km. The new data sets are first filtered using a dry-day adjustment. The simulations show a good agreement with observations for both statistical distributions and time series. Differences mainly appear in areas with sparse observation data. The temporal evolution during the past 60 years is well captured. The results reveal some long-term variability with phases of increased and decreased heavy precipitation. The overall trend varies between the investigation areas but is significant. The projections for the upcoming decade show ongoing tendencies with increased precipitation for upper percentiles. The presented RCM ensemble not only allows for more robust statistics in general, in particular it is suitable for a better estimation of extreme values.

Sign in / Sign up

Export Citation Format

Share Document