scholarly journals Effects of Land Surface Schemes on WRF-Simulated Geopotential Heights over China in Summer 2003*

2016 ◽  
Vol 17 (3) ◽  
pp. 829-851 ◽  
Author(s):  
Xin-Min Zeng ◽  
B. Wang ◽  
Y. Zhang ◽  
Y. Zheng ◽  
N. Wang ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Regional Climate ◽  
Sensible Heat Flux ◽  
Wrf Model ◽  
Surface Fluxes ◽  
Forecast Errors ◽  
Large Area ◽  
Pressure Fields ◽  
Temperature And Pressure

Abstract To quantify and explain effects of different land surface schemes (LSSs) on simulated geopotential height (GPH) fields, we performed simulations over China for the summer of 2003 using 12-member ensembles with the Weather Research and Forecasting (WRF) Model, version 3. The results show that while the model can generally simulate the seasonal and monthly mean GPH patterns, the effects of the LSS choice on simulated GPH fields are substantial, with the LSS-induced differences exceeding 10 gpm over a large area (especially the northwest) of China, which is very large compared with climate anomalies and forecast errors. In terms of the assessment measures for the four LSS ensembles [namely, the five-layer thermal diffusion scheme (SLAB), the Noah LSS (NOAH), the Rapid Update Cycle LSS (RUC), and the Pleim–Xiu LSS (PLEX)] in the WRF, the PLEX ensemble is the best, followed by the NOAH, RUC, and SLAB ensembles. The sensitivity of the simulated 850-hPa GPH is more significant than that of the 500-hPa GPH, with the 500-hPa GPH difference fields generally characterized by two large areas with opposite signs due to the smoothly varying nature of GPHs. LSS-induced GPH sensitivity is found to be higher than the GPH sensitivity induced by atmospheric boundary layer schemes. Moreover, theoretical analyses show that the LSS-induced GPH sensitivity is mainly caused by changes in surface fluxes (in particular, sensible heat flux), which further modify atmospheric temperature and pressure fields. The temperature and pressure fields generally have opposite contributions to changes in the GPH. This study emphasizes the importance of choosing and improving LSSs for simulating seasonal and monthly GPHs using regional climate models.

scholarly journals Regional Climate Variability Responses to Future Land Surface Forcing in the Brazilian Amazon

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Tao Zhang ◽  
Jinyan Zhan ◽  
Feng Wu ◽  
Jiao Luo ◽  
Juan Huang
Keyword(s):  
Heat Flux ◽  
Surface Temperature ◽  
Land Surface ◽  
Regional Climate ◽  
Sensible Heat Flux ◽  
Wrf Model ◽  
Brazilian Amazon ◽  
Close Link ◽  
Study Results ◽  
Surface Changes

Tropical deforestation could destabilize regional climate changes. This paper aimed to model the potential climatological variability caused by future forest vulnerability in the Brazilian Amazon over the 21th century. The underlying land surface changes between 2005 and 2100 are first projected based on the respectable output produced by Hurtt et al. Then the weather research and forecasting (WRF) model is applied to assess the impacts of future deforestation on regional climate during 2090–2100. The study results show that the forests in the Brazilian Amazon will primarily be converted into dryland cropland and pasture in the northwest part and into cropland/woodland mosaic in the southeast part, with 5.12% and 13.11%, respectively. These land surface changes will therefore lead to the significant reduction of the sum of sensible heat flux and latent heat flux and precipitation and the increase of the surface temperature. Furthermore, the variability of surface temperature is observed with close link to the deforested areas.

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.

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.

scholarly journals Effects of Forest Changes on Summer Surface Temperature in Changbai Mountain, China

Forests ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1551
Author(s):  
Jiaqi Zhang ◽  
Xiangjin Shen ◽  
Yanji Wang ◽  
Ming Jiang ◽  
Xianguo Lu
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Land Surface ◽  
Climate Models ◽  
Regional Climate ◽  
Changbai Mountain ◽  
Vegetation Coverage ◽  
Area Index ◽  
Forest Coverage ◽  
Cooling Effects

The area and vegetation coverage of forests in Changbai Mountain of China have changed significantly during the past decades. Understanding the effects of forests and forest coverage change on regional climate is important for predicting climate change in Changbai Mountain. Based on the satellite-derived land surface temperature (LST), albedo, evapotranspiration, leaf area index, and land-use data, this study analyzed the influences of forests and forest coverage changes on summer LST in Changbai Mountain. Results showed that the area and vegetation coverage of forests increased in Changbai Mountain from 2003 to 2017. Compared with open land, forests could decrease the summer daytime LST (LSTD) and nighttime LST (LSTN) by 1.10 °C and 0.07 °C, respectively. The increase in forest coverage could decrease the summer LSTD and LSTN by 0.66 °C and 0.04 °C, respectively. The forests and increasing forest coverage had cooling effects on summer temperature, mainly by decreasing daytime temperature in Changbai Mountain. The daytime cooling effect is mainly related to the increased latent heat flux caused by increasing evapotranspiration. Our results suggest that the effects of forest coverage change on climate should be considered in climate models for accurately simulating regional climate change in Changbai Mountain of China.

The Mesoscale Response to Global Warming over the Pacific Northwest Evaluated Using a Regional Climate Model Ensemble

2021 ◽  
pp. 1-56
Keyword(s):  
Global Warming ◽  
Pacific Northwest ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Wrf Model ◽  
Regional Climate Models ◽  
Winter Precipitation ◽  
Historical Period ◽  
Continental Interior

This paper describes the downscaling of an ensemble of twelve GCMs using the WRF model at 12-km grid spacing over the period 1970-2099, examining the mesoscale impacts of global warming as well as the uncertainties in its mesoscale expression. The RCP 8.5 emissions scenario was used to drive both global and regional climate models. The regional climate modeling system reduced bias and improved realism for a historical period, in contrast to substantial errors for the GCM simulations driven by lack of resolution. The regional climate ensemble indicated several mesoscale responses to global warming that were not apparent in the global model simulations, such as enhanced continental interior warming during both winter and summer as well as increasing winter precipitation trends over the windward slopes of regional terrain, with declining trends to the lee of major barriers. During summer there is general drying, except to the east of the Cascades. April 1 snowpack declines are large over the lower to middle slopes of regional terrain, with small snowpack increases over the lower elevations of the interior. Snow-albedo feedbacks are very different between GCM and RCM projections, with the GCM’s producing large, unphysical areas of snowpack loss and enhanced warming. Daily average winds change little under global warming, but maximum easterly winds decline modestly, driven by a preferential sea level pressure decline over the continental interior. Although temperatures warm continuously over the domain after approximately 2010, with slight acceleration over time, occurrences of temperature extremes increase rapidly during the second half of the 21st century.

scholarly journals Impact of humidity biases on light precipitation occurrence: observations versus simulations

2018 ◽  
Author(s):  
Sophie Bastin ◽  
Philippe Drobinski ◽  
Marjolaine Chiriaco ◽  
Olivier Bock ◽  
Romain Roehrig ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Regional Climate ◽  
Strong Dependence ◽  
Mediterranean Area ◽  
Critical Value ◽  
Critical Values ◽  
Frequency Of Occurrence ◽  
The Impact ◽  
Light Precipitation

Abstract. This work uses a network of GPS stations over Europe from which a homogenised integrated water vapor (IWV) dataset has been retrieved, completed with colocated temperature and precipitation measurements over specific stations to i) estimate the biases of six regional climate models over Europe in terms of humidity; ii) understand their origins; iii) and finally assess the impact of these biases on the frequency of occurrence of precipitation. The evaluated simulations have been performed in the framework of HYMEX/Med-CORDEX programs and cover the Mediterranean area and part of Europe at horizontal resolutions of 50 to 12 km. The analysis shows that models tend to overestimate the low values of IWV and the use of the nudging technique reduces the differences between GPS and simulated IWV. Results suggest that physics of models mostly explain the mean biases, while dynamics affects the variability. The land surface/atmosphere exchanges affect the estimation of IWV over most part of Europe, especially in summer. The limitations of the models to represent these processes explain part of their baises in IWV. However, models correctly simulate the dependance between IWV and temperature, and specifically the deviation that this relationship experiences regarding the Clausius-Clapeyron law after a critical value of temperature (Tbreak). The high spatial variability of Tbreak indicates that it has a strong dependence on local processes which drive the local humidity sources. This explains why the maximum values of IWV are not necessarely observed over warmer area, that are often dry area. Finally, it is shown over SIRTA observatory (near Paris) that the frequency of occurrence of light precipitation is strongly conditioned by the biases in IWV and by the precision of the models to reproduce the distribution of IWV as a function of the temperature. The results of the models indicate that a similar dependence occurs in other areas of Europe, especially where precipitation has a predominantly convective character. According to the observations, for each range of temperature, there is a critical value of IWV from which precipitation picks up. The critical values and the probability to exceed them are simulated with a bias that depends on the model. Those models which present too often light precipitation generally show lower critical values and higher probability to exceed them.

scholarly journals TopoSUB: a tool for efficient large area numerical modelling in complex topography at sub-grid scales

2012 ◽  
Vol 5 (5) ◽  
pp. 1245-1257 ◽  
Author(s):  
J. Fiddes ◽  
S. Gruber
Keyword(s):  
Numerical Modelling ◽  
Land Surface ◽  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Distributed Model ◽  
Heterogeneous Environments ◽  
Mountain Regions ◽  
Large Area ◽  
Fine Grid

Abstract. Mountain regions are highly sensitive to global climate change. However, large scale assessments of mountain environments remain problematic due to the high resolution required of model grids to capture strong lateral variability. To alleviate this, tools are required to bridge the scale gap between gridded climate datasets (climate models and re-analyses) and mountain topography. We address this problem with a sub-grid method. It relies on sampling the most important aspects of land surface heterogeneity through a lumped scheme, allowing for the application of numerical land surface models (LSMs) over large areas in mountain regions or other heterogeneous environments. This is achieved by including the effect of mountain topography on these processes at the sub-grid scale using a multidimensional informed sampling procedure together with a 1-D lumped model that can be driven by gridded climate datasets. This paper provides a description of this sub-grid scheme, TopoSUB, and assesses its performance against a distributed model. We demonstrate the ability of TopoSUB to approximate results simulated by a distributed numerical LSM at around 104 less computations. These significant gains in computing resources allow for: (1) numerical modelling of processes at fine grid resolutions over large areas; (2) efficient statistical descriptions of sub-grid behaviour; (3) a "sub-grid aware" aggregation of simulated variables to coarse grids; and (4) freeing of resources for computationally intensive tasks, e.g., the treatment of uncertainty in the modelling process.

scholarly journals Development of a Unified Land Model for Prediction of Surface Hydrology and Land–Atmosphere Interactions

2011 ◽  
Vol 12 (6) ◽  
pp. 1299-1320 ◽  
Author(s):  
Ben Livneh ◽  
Pedro J. Restrepo ◽  
Dennis P. Lettenmaier
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Climate Models ◽  
A Priori ◽  
Model Performance ◽  
Surface Flux ◽  
Surface Fluxes ◽  
Frozen Soil ◽  
Surface Model ◽  
Soil Moisture Accounting

Abstract A unified land model (ULM) is described that combines the surface flux parameterizations in the Noah land surface model (used in most of NOAA’s coupled weather and climate models) with the Sacramento Soil Moisture Accounting model (Sac; used for hydrologic prediction within the National Weather Service). The motivation was to develop a model that has a history of strong hydrologic performance while having the ability to be run in the coupled land–atmosphere environment. ULM takes the vegetation, snow model, frozen soil, and evapotranspiration schemes from Noah and merges them with the soil moisture accounting scheme from Sac. ULM surface fluxes, soil moisture, and streamflow simulations were evaluated through comparisons with observations from the Ameriflux (surface flux), Illinois Climate Network (soil moisture), and Model Parameter Estimation Experiment (MOPEX; streamflow) datasets. Initially, a priori parameters from Sac and Noah were used, which resulted in ULM surface flux simulations that were comparable to those produced by Noah (Sac does not predict surface energy fluxes). ULM with the a priori parameters had streamflow simulation skill that was generally similar to Sac’s, although it was slightly better (worse) for wetter (more arid) basins. ULM model performance using a set of parameters identified via a Monte Carlo search procedure lead to substantial improvements relative to the a priori parameters. A scheme for transfer of parameters from streamflow simulations to nearby flux and soil moisture measurement points was also evaluated; this approach did not yield conclusive improvements relative to the a priori parameters.

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 A Regional Climate Simulation Study Using WRF-ARW Model over Europe and Evaluation for Extreme Temperature Weather Events

2014 ◽  
Vol 2014 ◽  
pp. 1-22 ◽  
Author(s):  
Hari Prasad Dasari ◽  
Rui Salgado ◽  
Joao Perdigao ◽  
Venkata Srinivas Challa
Keyword(s):  
Land Surface ◽  
Heat Waves ◽  
Regional Climate ◽  
Extreme Temperature ◽  
Wrf Model ◽  
Initial Boundary ◽  
Analysis Data ◽  
Climate Simulation ◽  
Cold Wave ◽  
Local Climate

In this study regional climate simulations of Europe over the 60-year period (1950–2010) made using a 25 km resolution WRF model with NCEP 2.5 degree analysis for initial/boundary conditions are presented for air temperature and extreme events of heat and cold waves. The E-OBS 25 km analysis data sets are used for model validation. Results suggest that WRF could simulate the temperature trends (mean, maximum, minimum, seasonal maximum, and minimum) over most parts of Europe except over Iberian Peninsula, Mediterranean, and coastal regions. Model could simulate the slight fall of temperatures from 1950 to 1970 as well as steady rise in temperatures from 1970 to 2010 over Europe. Simulations show occurrence of about 80% of the total heat waves in the period 1970–2010 with maximum number of heat/cold wave episodes over Eastern and Central Europe in good agreement with observations. Relatively poor correlations and high bias are found for heat/cold wave episodes over the complex topographic areas of Iberia and Mediterranean regions where land surface processes play important role in local climate. The poor simulation of temperatures over the above regions could be due to deficiencies in representation of topography and surface physics which need further sensitivity studies.

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