Hydrological evaluation of high-resolution precipitation estimates from the WRF model in the Third Pole river basins

2021 ◽  
Author(s):  
He Sun ◽  
Fengge Su ◽  
Zhihua He ◽  
Tinghai Ou ◽  
Deliang Chen ◽  
...  
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Hydrological Modeling ◽  
Climate Model ◽  
Regional Climate ◽  
Wrf Model ◽  
Infiltration Capacity ◽  
Flood Prediction ◽  
Daily Streamflow ◽  
Precipitation Estimates

AbstractIn this study, two sets of precipitation estimates based on the regional Weather Research and Forecasting model (WRF) –the high Asia refined analysis (HAR) and outputs with a 9 km resolution from WRF (WRF-9km) are evaluated at both basin and point scales, and their potential hydrological utilities are investigated by driving the Variable Infiltration Capacity (VIC) large-scale land surface hydrological model in seven Third Pole (TP) basins. The regional climate model (RCM) tends to overestimate the gauge-based estimates by 20–95% in annual means among the selected basins. Relative to the gauge observations, the RCM precipitation estimates can accurately detect daily precipitation events of varying intensities (with absolute bias < 3 mm). The WRF-9km exhibits a high potential for hydrological application in the monsoon-dominated basins in the southeastern TP (with NSE of 0.7–0.9 and bias of -11% to 3%), while the HAR performs well in the upper Indus (UI) and upper Brahmaputra (UB) basins (with NSE of 0.6 and bias of -15% to -9%). Both the RCM precipitation estimates can accurately capture the magnitudes of low and moderate daily streamflow, but show limited capabilities in flood prediction in most of the TP basins. This study provides a comprehensive evaluation of the strength and limitation of RCMs precipitation in hydrological modeling in the TP with complex terrains and sparse gauge observations.

Configuration and Evaluation of the WRF Model for the Study of Hawaiian Regional Climate

2012 ◽  
Vol 140 (10) ◽  
pp. 3259-3277 ◽  
Author(s):  
Chunxi Zhang ◽  
Yuqing Wang ◽  
Axel Lauer ◽  
Kevin Hamilton
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Model Simulation ◽  
Regional Climate ◽  
Hawaiian Islands ◽  
Wrf Model ◽  
Trade Wind ◽  
Preliminary Evaluation ◽  
The Mean

Abstract The Weather Research and Forecasting (WRF) model V3.3 has been configured for the Hawaiian Islands as a regional climate model for the region (HRCM). This paper documents the model configuration and presents a preliminary evaluation based on a continuous 1-yr simulation forced by observed boundary conditions with 3-km horizontal grid spacing in the inner nested domain. The simulated vertical structure of the temperature and humidity are compared with twice-daily radiosonde observations at two stations. Generally the trade wind inversion (TWI) height and occurrence days are well represented. The simulation over the islands is compared with observations from nine surface climatological stations and a dense network of precipitation stations. The model simulation has generally small biases in the simulated surface temperature, relative humidity, and wind speed. The model realistically simulated the magnitude and geographical distribution of the mean rainfall over the Hawaiian Islands. In addition, the model simulation reproduced reasonably well the individual heavy rainfall events as seen from the time series of pentad mean rainfall averaged over island scales. Also the model reproduced the geographical variation of the mean diurnal rainfall cycle even though the observed diurnal cycle displays quite different features over different islands. Comparison with results obtained using the land surface dataset from the official release of the WRF model confirmed that the newly implemented land surface dataset generally improved the simulation of surface variables. These results demonstrate that the WRF can be a useful tool for dynamical downscaling of regional climate over the Hawaiian Islands.

scholarly journals Evaluation of convective parameters derived from pressure level and native ERA5 data and different resolution WRF climate simulations over Central Europe

2021 ◽  
Author(s):  
Ákos János Varga ◽  
Hajnalka Breuer
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Wrf Model ◽  
Environmental Parameters ◽  
Pressure Level ◽  
Lapse Rate ◽  
Strong Suppression ◽  
Climate Simulations ◽  
Multiple Variables

AbstractThe mean climatological distribution of convective environmental parameters from the ERA5 reanalysis and WRF regional climate simulations is evaluated using radiosonde observations. The investigation area covers parts of Central and Eastern Europe. Severe weather proxies are calculated from daily 1200 UTC sounding measurements and collocated ERA5 and WRF pseudo-profiles in the 1985–2010 period. The pressure level and the native ERA5 reanalysis, and two WRF runs with grid spacings of 50 and 10 km are verified. ERA5 represents convective parameters remarkably well with correlation coefficients higher than 0.9 for multiple variables and mean errors close to zero for precipitable water and mid-tropospheric lapse rate. Monthly mean mixed-layer CAPE biases are reduced in the full hybrid-sigma ERA5 dataset by 20–30 J/kg compared to its pressure level version. The WRF model can reproduce the annual cycle of thunderstorm predictors but with considerably lower correlations and higher errors than ERA5. Surface elevation differences between the stations and the corresponding grid points in the 50-km WRF run lead to biases and false error compensations in the convective indices. The 10-km grid spacing is sufficient to avoid such discrepancies. The evaluation of convection-related parameters contributes to a better understanding of regional climate model behavior. For example, a strong suppression of convective activity might explain precipitation underestimation in summer. A decreasing correlation of WRF-derived wind shear away from the western domain boundaries indicates a deterioration of the large-scale circulation as the constraining effect of the driving reanalysis weakens.

scholarly journals Land surface model influence on the simulated climatologies of temperature and precipitation extremes in the WRF v3.9 model over North America

2020 ◽  
Vol 13 (11) ◽  
pp. 5345-5366
Author(s):  
Almudena García-García ◽  
Francisco José Cuesta-Valero ◽  
Hugo Beltrami ◽  
Fidel González-Rouco ◽  
Elena García-Bustamante ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Extreme Temperature ◽  
Wrf Model ◽  
Land Surface Model ◽  
Surface Model ◽  
Temperature And Precipitation ◽  
Model Ensembles ◽  
Precipitation Events

Abstract. The representation and projection of extreme temperature and precipitation events in regional and global climate models are of major importance for the study of climate change impacts. However, state-of-the-art global and regional climate model simulations yield a broad inter-model range of intensity, duration and frequency of these extremes. Here, we present a modeling experiment using the Weather Research and Forecasting (WRF) model to determine the influence of the land surface model (LSM) component on uncertainties associated with extreme events. First, we analyze land–atmosphere interactions within four simulations performed by the WRF model from 1980 to 2012 over North America, using three different LSMs. Results show LSM-dependent differences at regional scales in the frequency of occurrence of events when surface conditions are altered by atmospheric forcing or land processes. The inter-model range of extreme statistics across the WRF simulations is large, particularly for indices related to the intensity and duration of temperature and precipitation extremes. Our results show that the WRF simulation of the climatology of heat extremes can be 5 ∘C warmer and 6 d longer depending on the employed LSM component, and similarly for cold extremes and heavy precipitation events. Areas showing large uncertainty in WRF-simulated extreme events are also identified in a model ensemble from three different regional climate model (RCM) simulations participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX) project, revealing the implications of these results for other model ensembles. Thus, studies based on multi-model ensembles and reanalyses should include a variety of LSM configurations to account for the uncertainty arising from this model component or to test the performance of the selected LSM component before running the whole simulation. This study illustrates the importance of the LSM choice in climate simulations, supporting the development of new modeling studies using different LSM components to understand inter-model differences in simulating extreme temperature and precipitation events, which in turn will help to reduce uncertainties in climate model projections.

Modeling the Influence of Upstream Land-atmosphere Coupling on the 2017 Persistent Drought over Northeast China

2021 ◽  
pp. 1-62
Author(s):  
Dingwen Zeng ◽  
Xing Yuan
Keyword(s):  
Land Surface ◽  
Northeast China ◽  
Large Scale ◽  
Climate Modeling ◽  
Regional Climate ◽  
Critical Role ◽  
Wrf Model ◽  
Regional Climate Modeling ◽  
Anticyclonic Circulation ◽  
Persistent Drought

AbstractPersistent drought events that cause serious damages to economy and environment are usually intensified by the feedback between land surface and atmosphere. Therefore, reasonably modeling land-atmosphere coupling is critical for skillful prediction of persistent droughts. However, most high-resolution regional climate modeling focused on the amplification effect of land-atmosphere coupling on local anticyclonic circulation anomaly, while less attention was paid to the non-local influence through altering large-scale atmospheric circulation. Here we investigate how the antecedent land-atmosphere coupling over the area south to Lake Baikal (ASLB) influences the drought events occurred over its downstream region (Northeast China; NEC) by using Weather Research and Forecasting (WRF) model and linear baroclinic model (LBM). When the ASLB is artificially forced to be wet in the WRF simulations during March-May, the surface sensible heating is weakened and results in a cooling anomaly in low level atmosphere during May-July. Consequently, the anticyclonic circulation anomalies over ASLB and NEC are weakened, and the severity of NEC drought during May-July cannot be captured due to the upstream wetting in March-May. In the LBM experiments, idealized atmospheric heating anomaly that mimics the diabatic heating associated with surface wetness is imposed over ASLB, and the quasi-steady response pattern of 500-hPa geopotential height to the upstream wetting is highly consistent with that in the WRF simulation. In addition, the lower level heating instead of the upper level cooling makes a major contribution to the high pressure anomaly over NEC. This study implies the critical role of modeling upstream land-atmosphere coupling in capturing downstream persistent droughts.

High Resolution WRF Regional Climate Modeling for the Andes-Amazon Transition Region: Model Validation Early Results

2020 ◽  
Author(s):  
Juan Pablo Sierra ◽  
Clementine Junquas ◽  
Jhan Carlo Epinoza ◽  
Thierry Lebel ◽  
Hans Segura
Keyword(s):  
High Resolution ◽  
Transition Region ◽  
Land Surface ◽  
Large Scale ◽  
Amazon Basin ◽  
Climate Model ◽  
Rainfall Variability ◽  
Regional Climate ◽  
The Andes ◽  
Early Results

&lt;p&gt;&lt;span&gt;The western Amazon and eastern flank of the Andes form what is known as the Amazon-Andes transition region. This region is characterized by the presence of the rainiest area in the Amazon basin with an average precipitation ranging from 6000 to 7000 mm per year. This rainy zone is the result of interactions between large-scale circulation and local features. However, the physical mechanisms controlling this rainfall patterns in the transition region are poorly understood. On the other hand, high precipitation values in the area, along with erosion, sediment transport and the geological mountain uplift help to explain this region as one of the most species-rich terrestrial ecosystems. Nevertheless, accelerated deforestation rates reported both in tropical Andes and central-southern Amazon threat the biodiversity hotspots and can induce alterations in land surface energy and water balances. In this context, the use of regional climate models can shed light on the possible consequences of deforestation on rainfall in the transition region. &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;The early results presented here are the first step in a work that seeks to gain a better understanding in the mechanisms involved in precipitation generation over the Amazon-Andes transition region, as well as the assessment of deforestation impacts on spatial and temporal rainfall variability during austral summer. The Weather Research and Forecasting (WRF) regional climate model is used with three nested domains. High resolution simulations (1km horizontal grid size) are performed over the key regions of Cuzco and Bolivian slopes. As a perspective,&lt;span&gt;&amp;#160; &lt;/span&gt;deforestation scenarios following the land use change trajectory observed during the last decade will be used in future works. The results of this work can help to dimension the consequences of deforestation on key ecosystems such as Andean hotspots.&lt;/span&gt;&lt;/p&gt;

scholarly journals Simulation of summer climate over Central Asia shows high sensitivity to different land surface schemes in WRF

2021 ◽  
Author(s):  
Sha Lu ◽  
Weidong Guo ◽  
Yongkang Xue ◽  
Fang Huang ◽  
Jun Ge
Keyword(s):  
Central Asia ◽  
Land Surface ◽  
Large Scale ◽  
Climate Models ◽  
Global Analysis ◽  
Regional Climate ◽  
Wrf Model ◽  
Heat Fluxes ◽  
Ensemble Average ◽  
Adjustment Process

AbstractLand surface processes are vital to the performance of regional climate models in dynamic downscaling application. In this study, we investigate the sensitivity of the simulation by using the weather research and forecasting (WRF) model at 10-km resolution to the land surface schemes over Central Asia. The WRF model was run for 19 summers from 2000 to 2018 configured with four different land surface schemes including CLM4, Noah-MP, Pleim-Xiu and SSiB, hereafter referred as Exp-CLM4, Exp-Noah-MP, Exp-PX and Exp-SSiB respectively. The initial and boundary conditions for the WRF model simulations were provided by the National Centers for Environmental Prediction Final (NCEP-FNL) Operational Global Analysis data. The ERA-Interim reanalysis (ERAI), the GHCN-CAMS and the CRU gridded data were used to comprehensively evaluate the WRF simulations. Compared with the reanalysis and observational data, the WRF model can reasonably reproduce the spatial patterns of summer mean 2-m temperature, precipitation, and large- scale atmospheric circulation. The simulations, however, are sensitive to the option of land surface scheme. The performance of Exp-CLM4 and Exp-SSiB are better than that of Exp-Noah-MP and Exp-PX assessed by Multivariable Integrated Evaluation (MVIE) method. To comprehensively understand the dynamic and physical mechanisms for the WRF model’s sensitivity to land surface schemes, the differences in the surface energy balance between Ave-CLM4-SSiB (the ensemble average of Exp-CLM4 and Exp-SSiB) and Ave-NoanMP-PX (the ensemble average of Exp-Noah-MP and Exp-PX) are analyzed in detail. The results demonstrate that the sensible and latent heat fluxes are respectively lower by 30.42 W·m−2 and higher by 14.86 W·m−2 in Ave-CLM4-SSiB than that in Ave-NoahMP-PX. As a result, large differences in geopotential height occur over the simulation domain. The simulated wind fields are subsequently influenced by the geostrophic adjustment process, thus the simulations of 2-m temperature, surface skin temperature and precipitation are respectively lower by about 2.08 ℃, 2.23 ℃ and 18.56 mm·month−1 in Ave-CLM4-SSiB than that in Ave-NoahMP-PX over Central Asia continent.

scholarly journals Land Surface Model influence on the simulated climatologies of temperature and precipitation extremes in the WRF v.3.9 model over North America

2020 ◽  
Author(s):  
Almudena García-García ◽  
Francisco José Cuesta-Valero ◽  
Hugo Beltrami ◽  
J. Fidel González-Rouco ◽  
Elena García-Bustamante ◽  
...  
Keyword(s):  
North America ◽  
Regional Climate Model ◽  
Extreme Events ◽  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Wrf Model ◽  
Land Surface Model ◽  
Surface Model ◽  
Temperature And Precipitation

Abstract. The representation and projection of extreme temperature and precipitation events in regional and global climate models are of major importance for the study of climate change impacts. However, state-of-the-art global and regional climate model simulations yield a broad inter-model range of intensity, duration and frequency of these extremes. Here, we present a modeling experiment using the Weather Research and Forecasting (WRF) model to determine the influence of the land surface model (LSM) component on uncertainties associated with extreme events. First, we evaluate land-atmosphere interactions within four simulations performed by the WRF model using three different LSMs from 1980 to 2012 over North America. Results show LSM-dependent differences at regional scales in the frequency of occurrence of events when surface conditions are altered by atmospheric forcing or land processes. The inter-model range of extreme statistics across the WRF simulations is large, particularly for indices related to the intensity and duration of temperature and precipitation extremes. Areas showing large uncertainty in WRF simulated extreme events are also identified in a model ensemble from three different Regional Climate Model (RCM) simulations participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX) project, revealing the implications of these results for other model ensembles. This study illustrates the importance of the LSM choice in climate simulations, supporting the development of new modeling studies using different LSM components to understand inter-model differences in simulating temperature and precipitation extreme events, which in turn will help to reduce uncertainties in climate model projections.

Land Surface Model influence on the simulated climatologies of extreme temperature and precipitation events within the WRF model over North America

2020 ◽  
Author(s):  
Almudena García-García ◽  
Francisco José Cuesta-Valero ◽  
Hugo Beltrami ◽  
J. Fidel González-Rouco ◽  
Elena García-Bustamante ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Extreme Temperature ◽  
Wrf Model ◽  
Land Surface Model ◽  
Surface Model ◽  
Model Simulations ◽  
Temperature And Precipitation ◽  
Precipitation Events

&lt;p class=&quot;western&quot;&gt;&lt;span&gt;The representation and projection of extreme temperature and precipitation events in climate models are of major importance for developing polices to build communities&amp;#8217; resilience in the face of climate change. However, state-of-the-art global and regional climate model simulations yield a broad inter-model range of intensities, durations and frequencies of these extremes. &lt;/span&gt;&lt;/p&gt; &lt;p class=&quot;western&quot;&gt;&lt;span&gt;Here, we present a modeling experiment using the Weather Research and Forecasting (WRF) Regional Climate Model (RCM) to determine the influence of the choice of land surface model (LSM) component on the uncertainty in the simulation of extreme event statistics. First, we evaluate land-atmosphere interactions within four simulations performed with the WRF model coupled to three different LSMs from 1980 to 2012 over North America. Results show regional differences among simulations for the frequency of events when surface conditions are altered by atmospheric forcing or by land surface processes. Second, we find a large inter-model range of extreme statistics across the ensemble of WRF-LSM simulations. This is particularly the case for indices related to the intensity and duration of temperature and precipitation extremes. &lt;/span&gt;&lt;/p&gt; &lt;p class=&quot;western&quot;&gt;&lt;span&gt;Regions displaying large uncertainty in the WRF simulation of extreme events are also identified in a model ensemble experiment carried out with three different RCMs participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX) project. This agreement between the model simulations performed in this work and the set of CORDEX simulations suggests that the implications of our results are valid for other model ensembles. This study illustrates the importance of supporting the development of new multi-LSM modeling studies to understand inter-model differences in simulating extreme events, ultimately helping to narrow down the range across climate model projections.&lt;/span&gt;&lt;/p&gt;

Varying horizontal resolution and land surface schemes in soil moisture – air temperature coupling, calculated with the WRF model for the MENA-CORDEX domain

2021 ◽  
Author(s):  
Katiana Constantinidou ◽  
Panos Hadjinicolaou ◽  
George Zittis ◽  
Jos Lelieveld
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Wrf Model ◽  
Correlation Coefficients ◽  
Horizontal Resolution ◽  
Western Asia ◽  
June July

&lt;p&gt;We study the effect of increased resolution and more elaborate representation of land surface on the soil moisture &amp;#8211; air temperature coupling with the WRF climate downscaling model. Previous work indicated reduced winter/spring rainfall and enhanced summer heat. Two different land surface schemes (LSS) Noah and NoahMP with dynamic vegetation option turned on are incorporated in the WRF regional climate model in simulations at 50 and 16 km horizontal resolution over the region of Middle East and North Africa (MENA) for the period of 2000-2004. An analysis is performed for the summer season (June-July-August; JJA) for the four-year period, employing coupling metrics, i.e. associations between climatic variables related to the soil moisture &amp;#8211; air temperature coupling. We calculate correlation coefficients between time-series consisting of 10-day averages, non-overlapping, for related surface climate variables from the WRF simulations and observational datasets. This assessment indicates that the NoahMP scheme simulates a stronger coupling than the Noah, irrespective of the resolution. The strength of this coupling varies at different areas around the MENA when considering mean or maximum 2-meter air temperature, with the NoahMP at 16-km producing the strongest effect over the western Asia part of the domain.&lt;/p&gt;

Sign in / Sign up

Export Citation Format

Share Document