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.

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.

Impact of Soil Moisture Initialization on Temperature Extreme Detection in the context of Regional Climate Modeling

2020 ◽  
Author(s):  
Matilde García-Valdecasas Ojeda ◽  
Juan José Rosa-Cánovas ◽  
Emilio Romero-Jiménez ◽  
Patricio Yeste ◽  
Sonia R. Gámiz-Fortis ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Initial Conditions ◽  
Climate Modeling ◽  
Regional Climate ◽  
Wrf Model ◽  
Regional Climate Modeling ◽  
Weather Research And Forecasting ◽  
Temperature Extremes ◽  
Temperature Extreme ◽  
The Impact

&lt;p&gt;Land surface-related processes play an essential role in the climate conditions at a regional scale. In this study, the impact of soil moisture (SM) initialization on regional climate modeling has been explored by using a dynamical downscaling experiment. To this end, the Weather Research and Forecasting (WRF) model was used to generate a set of high-resolution climate simulations driven by the ERA-Interim reanalysis for a period from 1989 to 2009. As the spatial configuration, two one-way nested domains were used, with the finer domain being centered over the Iberian Peninsula (IP) at a spatial resolution of about 10 km, and nested over a coarser domain that covers the Euro-CORDEX region at 50 km of spatial resolution.&lt;/p&gt;&lt;p&gt;The sensitivity experiment consisted of two control runs (CTRL) performed using as SM initial conditions those provided by ERA-Interim, and initialized for two different dates times (January and June). Additionally, another set of runs was completed driven by the same climate data but using as initial conditions prescribed SM under wet and dry scenarios.&lt;/p&gt;&lt;p&gt;The study is based on assessing the WRF performance by comparing the CTRL simulations with those performed with the different prescribed SM, and also, comparing them with the observations from the Spanish Temperature At Daily scale (STEAD) dataset. In this sense, we used two temperature extreme indices within the framework of decadal predictions: the warm spell index (WSDI) and the daily temperature range (DTR).&lt;/p&gt;&lt;p&gt;These results provide valuable information about the impact of the SM initial conditions on the ability of the WRF model to detect temperature extremes, and how long these affect the regional climate in this region. Additionally, these results may provide a source of knowledge about the mechanisms involved in the occurrence of extreme events such as heatwaves, which are expected to increase in frequency, duration, and magnitude under the context of climate change.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Keywords&lt;/strong&gt;: soil moisture initial conditions, temperature extremes, regional climate, Weather Research and Forecasting model&lt;/p&gt;&lt;p&gt;Acknowledgments: This work has been financed by the project CGL2017-89836-R (MINECO-Spain, FEDER). The WRF simulations were performed in the Picasso Supercomputer at the University of M&amp;#225;laga, a member of the Spanish Supercomputing Network.&lt;/p&gt;

scholarly journals Sensitivity of physical parameterization schemes in WRF model for dynamic downscaling of climatic variables over the MRB

2020 ◽  
Author(s):  
Lia Pervin ◽  
Thian Yew Gan
Keyword(s):  
Land Surface ◽  
Reference Data ◽  
Climate Modeling ◽  
Regional Climate ◽  
Wrf Model ◽  
Climatic Variables ◽  
Surface Physics ◽  
Dynamic Downscaling ◽  
Radiation Physics ◽  
Mountainous Regions

Abstract The Weather Research and Forecasting (WRF) model was tested through 18 different combinations of physics parameters to simulate the regional climate over the Mackenzie River Basin (MRB). The objective was to investigate the response to the physics parameters for dynamic downscaling of climatic variables. The rainfall, temperature, albedo, and surface pressure from the 18 different WRF setups were compared with the reference data and were found sensitive to land surface physics and microphysics and to the radiation physics. The combination of Noah Land Surface Physics with the WRF Single-moment 6-class microphysics and CAM shortwave and longwave schemes produced comparable results for summer 2009. This WRF setup was further tested for summers 1979–1991 and it was found that WRF could simulate air temperature more accurately than the rainfall, since the rainfall over the mountainous regions was over-simulated. Then the selected combinations of WRF parameterizations were used to downscale the CanESM2 historical temperature and rainfall for summers 1979–2005, which showed good agreement with the reference data. The suggested WRF parameters from this study could be utilized for regional climate modeling of MRB.

scholarly journals Examining Interior Grid Nudging Techniques Using Two-Way Nesting in the WRF Model for Regional Climate Modeling

2012 ◽  
Vol 25 (8) ◽  
pp. 2805-2823 ◽  
Author(s):  
Jared H. Bowden ◽  
Tanya L. Otte ◽  
Christopher G. Nolte ◽  
Martin J. Otte
Keyword(s):  
Climate Modeling ◽  
Regional Climate ◽  
Wrf Model ◽  
Regional Climate Modeling ◽  
Atmospheric Model ◽  
Meridional Wind ◽  
Department Of Energy ◽  
Monthly Precipitation ◽  
Spectral Nudging ◽  
Regional Reanalysis

Abstract This study evaluates interior nudging techniques using the Weather Research and Forecasting (WRF) model for regional climate modeling over the conterminous United States (CONUS) using a two-way nested configuration. NCEP–Department of Energy Atmospheric Model Intercomparison Project (AMIP-II) Reanalysis (R-2) data are downscaled to 36 km × 36 km by nudging only at the lateral boundaries, using gridpoint (i.e., analysis) nudging and using spectral nudging. Seven annual simulations are conducted and evaluated for 1988 by comparing 2-m temperature, precipitation, 500-hPa geopotential height, and 850-hPa meridional wind to the 32-km North American Regional Reanalysis (NARR). Using interior nudging reduces the mean biases for those fields throughout the CONUS compared to the simulation without interior nudging. The predictions of 2-m temperature and fields aloft behave similarly when either analysis or spectral nudging is used. For precipitation, however, analysis nudging generates monthly precipitation totals, and intensity and frequency of precipitation that are closer to observed fields than spectral nudging. The spectrum of 250-hPa zonal winds simulated by the WRF model is also compared to that of the R-2 and NARR. The spatial variability in the WRF model is reduced by using either form of interior nudging, and analysis nudging suppresses that variability more strongly than spectral nudging. Reducing the nudging strengths on the inner domain increases the variability but generates larger biases. The results support the use of interior nudging on both domains of a two-way nest to reduce error when the inner nest is not otherwise dominated by the lateral boundary forcing. Nevertheless, additional research is required to optimize the balance between accuracy and variability in choosing a nudging strategy.

scholarly journals Crossing Multiple Gray Zones in the Transition from Mesoscale to Microscale Simulation over Complex Terrain

Atmosphere ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 274 ◽  
Author(s):  
Fotini Chow ◽  
Christoph Schär ◽  
Nikolina Ban ◽  
Katherine Lundquist ◽  
Linda Schlemmer ◽  
...  
Keyword(s):  
Complex Terrain ◽  
Large Scale ◽  
Climate Modeling ◽  
Numerical Models ◽  
Weather Prediction ◽  
Regional Climate ◽  
Regional Climate Modeling ◽  
Small Scale ◽  
Gray Zone ◽  
Definition Of

This review paper explores the field of mesoscale to microscale modeling over complex terrain as it traverses multiple so-called gray zones. In an attempt to bridge the gap between previous large-scale and small-scale modeling efforts, atmospheric simulations are being run at an unprecedented range of resolutions. The gray zone is the range of grid resolutions where particular features are neither subgrid nor fully resolved, but rather are partially resolved. The definition of a gray zone depends strongly on the feature being represented and its relationship to the model resolution. This paper explores three gray zones relevant to simulations over complex terrain: turbulence, convection, and topography. Taken together, these may be referred to as the gray continuum. The focus is on horizontal grid resolutions from ∼10 km to ∼10 m. In each case, the challenges are presented together with recent progress in the literature. A common theme is to address cross-scale interaction and scale-awareness in parameterization schemes. How numerical models are designed to cross these gray zones is critical to complex terrain applications in numerical weather prediction, wind resource forecasting, and regional climate modeling, among others.

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 Changes in Hurricanes from a 13-Yr Convection-Permitting Pseudo–Global Warming Simulation

2018 ◽  
Vol 31 (9) ◽  
pp. 3643-3657 ◽  
Author(s):  
Ethan D. Gutmann ◽  
Roy M. Rasmussen ◽  
Changhai Liu ◽  
Kyoko Ikeda ◽  
Cindy L. Bruyere ◽  
...  
Keyword(s):  
Tropical Cyclones ◽  
Climate Modeling ◽  
Global Climate ◽  
Regional Climate ◽  
Good Reason ◽  
Wrf Model ◽  
Coupled Model ◽  
Regional Climate Modeling ◽  
Climate Signal ◽  
Wind Speeds

Abstract Tropical cyclones have enormous costs to society through both loss of life and damage to infrastructure. There is good reason to believe that such storms will change in the future as a result of changes in the global climate system and that such changes may have important socioeconomic implications. Here a high-resolution regional climate modeling experiment is presented using the Weather Research and Forecasting (WRF) Model to investigate possible changes in tropical cyclones. These simulations were performed for the period 2001–13 using the ERA-Interim product for the boundary conditions, thus enabling a direct comparison between modeled and observed cyclone characteristics. The WRF simulation reproduced 30 of the 32 named storms that entered the model domain during this period. The model simulates the tropical cyclone tracks, storm radii, and translation speeds well, but the maximum wind speeds simulated were less than observed and the minimum central pressures were too large. This experiment is then repeated after imposing a future climate signal by adding changes in temperature, humidity, pressure, and wind speeds derived from phase 5 of the Coupled Model Intercomparison Project (CMIP5). In the current climate, 22 tracks were well simulated with little changes in future track locations. These simulations produced tropical cyclones with faster maximum winds, slower storm translation speeds, lower central pressures, and higher precipitation rates. Importantly, while these signals were statistically significant averaged across all 22 storms studied, changes varied substantially between individual storms. This illustrates the importance of using a large ensemble of storms to understand mean changes.

Lateral boundary relaxation and large scale nudging in RCM runs

2020 ◽  
Author(s):  
Fedor Mesinger ◽  
Katarina Veljovic ◽  
Sin Chan Chou
Keyword(s):  
Large Scale ◽  
Climate Modeling ◽  
Regional Climate ◽  
Regional Climate Modeling ◽  
Scientific Basis ◽  
Driver Model ◽  
Limited Area ◽  
Lateral Boundary ◽  
Limited Area Model ◽  
Area Model

&lt;p&gt;Almost universally, in Regional Climate Modeling (RCM) integrations, Davies&amp;#8217; relaxation lateral boundary conditions are applied. They force variables in a number of rows around the boundary to conform to the driver global model values, completely at the boundary, and less and less toward the inside of the integration domain. Very often, in addition, investigators apply so-called large scale or spectral nudging inside the domain, forcing the integration variables not to depart much from those of the driver model.&lt;/p&gt;&lt;p&gt;It is pointed out that there is no scientific basis for these two practices. So why are they used? In particular for the former of these two, it is suggested that reasons must be either a belief that this is a practice RCM should follow, or a technique to address numerical issues of the limited area model used, or a combination of the two.&amp;#160; For the latter, a belief only.&lt;/p&gt;&lt;p&gt;Examples are shown that, in the absence of these two stratagems, the limited area model can improve on large scales inside its domain. This demonstrates that their use, aimed to force variables inside the domain not to depart much from the driver model data, should be detrimental, if possible numerical issues of the model used were to be remedied.&lt;/p&gt;

scholarly journals Urban Climates and Climate Change

2020 ◽  
Vol 45 (1) ◽  
pp. 411-444 ◽  
Author(s):  
Valéry Masson ◽  
Aude Lemonsu ◽  
Julia Hidalgo ◽  
James Voogt
Keyword(s):  
Climate Change ◽  
Climate Modeling ◽  
Regional Climate ◽  
Urban Climate ◽  
Regional Climate Modeling ◽  
Climate Impact ◽  
Local Climate ◽  
Urban Climatology ◽  
Recent Developments ◽  
Global Agenda

Cities are particularly vulnerable to extreme weather episodes, which are expected to increase with climate change. Cities also influence their own local climate, for example, through the relative warming known as the urban heat island (UHI) effect. This review discusses urban climate features (even in complex terrain) and processes. We then present state-of-the-art methodologies on the generalization of a common urban neighborhood classification for UHI studies, as well as recent developments in observation systems and crowdsourcing approaches. We discuss new modeling paradigms pertinent to climate impact studies, with a focus on building energetics and urban vegetation. In combination with regional climate modeling, new methods benefit the variety of climate scenarios and models to provide pertinent information at urban scale. Finally, this article presents how recent research in urban climatology contributes to the global agenda on cities and climate change.

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