WRF Sensitivity for Seasonal Climate Simulations of Precipitation Fields on the CORDEX South America Domain

Dynamic numerical models of the atmosphere are the main tools used for weather and climate forecasting as well as climate projections. Thus, this work evaluated the systematic errors and areas with large uncertainties in precipitation over the South American continent (SAC) based on regional climate simulations with the weather research and forecasting (WRF) model. Ten simulations using different convective, radiation, and microphysical schemes, and an ensemble mean among them, were performed with a resolution of 50 km, covering the CORDEX-South America domain. First, the seasonal precipitation variability and its differences were discussed. Then, its annual cycle was investigated through nine sub-domains on the SAC (AMZN, AMZS, NEBN, NEBS, SE, SURU, CHAC, PEQU, and TOTL). The Taylor Diagrams were used to assess the sensitivity of the model to different parameterizations and its ability to reproduce the simulated precipitation patterns. The results showed that the WRF simulations were better than the ERA-interim (ERAI) reanalysis when compared to the TRMM, showing the added value of dynamic downscaling. For all sub-domains the best result was obtained with the ensemble compared to the satellite TRMM. The largest errors were observed in the SURU and CHAC regions, and with the greatest dispersion of members during the rainy season. On the other hand, the best results were found in the AMZS, NEBS, and TOTL regions.

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Regional climate simulations at kilometer-scale with RegCM4: Evaluation of precipitation and future projections

10.5194/egusphere-egu2020-9183 ◽

2020 ◽

Author(s):

Paolo Stocchi ◽

Emanuela Pichelli ◽

Erika Coppola ◽

Jose Abraham Torres Alvarez ◽

Filippo Giorgi

Keyword(s):

Global Climate Model ◽

Regional Climate ◽

Added Value ◽

Historical Period ◽

Climate Projections ◽

Model Errors ◽

Grid Spacing ◽

Climate Simulations ◽

Near Future ◽

Far Future

<p>The recent increase in climate modeling activities at convection permitting scales (grid spacing under 4 km) has strongly been motivated by the increased computer capacities in the last years with the aim to reduce the model errors associated with parameterized convection and a more detailed representation of present and future regional climate. Some Regional climate projects addressing on convection permitting modeling simulations and projections have been recently implemented to make more robust conclusions on the added value of convection permitting simulation to future climate projections. Here, we present convection resolving climate simulations performed in the framework the European Climate Prediction System (EUCP) project, using the non-hydrostatic version of the RegCM model. The RegCM simulations have a grid spacing of 3 km, over three different regions (Pan-Alpine, Central Europe, and South-East Europe). These simulations were driven by initial and boundary conditions built from intermediate 12 km simulations driven by the global climate model (GCM) HadGEM2-ES. We considered three time slices each one of them covering a 10-year period, the historical (1996-2005), the near future (2041-2050) and the far future (2090-2099) under the RCP8.5 scenario. The high resolutions (3 km) simulations, over the historical period, are evaluated through comparison with available observations data sets (including in-situ and satellite-based observation of precipitation) and coarse resolution (12 km) simulation is used as benchmark. The kilometer-scale RegCM4.7 scenario (RCP8.5) simulations, driven by HadGEM2-ES, near future (2041-2050) and the far future (2090-2099), are also analyzed and presented, focusing on the future change in terms of mean precipitation, precipitation intensity and frequency and heavy precipitation on daily and hourly timescales in different seasons.</p>

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Effects of Surface Coupling Strength in WRF/Noah-MP Model on Regional Climate Simulations Over China

10.21203/rs.3.rs-221209/v1 ◽

2021 ◽

Author(s):

Xia Zhang ◽

Liang Chen ◽

Zhuguo Ma ◽

Jianping Duan ◽

Danqiong Dai ◽

...

Keyword(s):

Coupling Strength ◽

Land Surface ◽

Numerical Models ◽

Exchange Process ◽

Regional Climate ◽

Surface Fluxes ◽

Surface Model ◽

Surface Exchange ◽

Climate Simulations ◽

Simulated Precipitation

Abstract Land–atmosphere energy and moisture exchange can strongly influence local and regional climate. However, high uncertainty exits in the representation of land–atmosphere interactions in numerical models. The parameterization of surface exchange process is greatly affected by varying the parameter Czil which, however, is typically set to a domain-wide constant value. In this study, we examine the sensitivity of regional climate simulations over China to different surface exchange strengths using three Czil schemes (default without Czil , constant Czil = 0.1, and dynamic canopy-height-dependent Czil -h schemes) in the 13-km-resolution Weather Research and Forecasting model coupled with a Noah land surface model with multi-parameterization options (WRF/Noah-MP). Our results demonstrate that the Czil -h scheme substantially reduces the overestimations of land–atmosphere coupling strength in the other two schemes, and comparisons with the ChinaFLUX observations indicate the capability of the Czil -h scheme to better match the observed surface energy and water variations. The results of the Czil schemes applying to four typical climate zones of China present that the Czil -h simulations are in the closest agreements with the field observations. The Czil -h scheme can narrow the positive discrepancies of simulated precipitation and surface fluxes as well as the negative biases of Ts in areas of Northeast, North China, Eastern Northwest, and Southwest. Especially, the above remarkable improvements produced by the Czil -h scheme are primarily over areas covering short vegetation. Also noted that the precipitation simulated by the Czil -h scheme exhibits more intricate and unclear changes compared with surface fluxes simulations due to the non-local impacts of surface exchange strength resulted from the fluidity of the atmosphere. Overall, our findings highlight the applicability of the dynamical Czil as a better physical alternative to treat the surface exchange process in atmosphere coupling models.

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Precipitation Climatology in an Ensemble of CORDEX-Africa Regional Climate Simulations

Journal of Climate ◽

10.1175/jcli-d-11-00375.1 ◽

2012 ◽

Vol 25 (18) ◽

pp. 6057-6078 ◽

Cited By ~ 358

Author(s):

Grigory Nikulin ◽

Colin Jones ◽

Filippo Giorgi ◽

Ghassem Asrar ◽

Matthias Büchner ◽

...

Keyword(s):

Diurnal Cycle ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Models ◽

Small Subset ◽

Climate Projections ◽

Systematic Bias ◽

Diurnal Cycles ◽

Climate Simulations ◽

Simulated Precipitation

Abstract An ensemble of regional climate simulations is analyzed to evaluate the ability of 10 regional climate models (RCMs) and their ensemble average to simulate precipitation over Africa. All RCMs use a similar domain and spatial resolution of ~50 km and are driven by the ECMWF Interim Re-Analysis (ERA-Interim) (1989–2008). They constitute the first set of simulations in the Coordinated Regional Downscaling Experiment in Africa (CORDEX-Africa) project. Simulated precipitation is evaluated at a range of time scales, including seasonal means, and annual and diurnal cycles, against a number of detailed observational datasets. All RCMs simulate the seasonal mean and annual cycle quite accurately, although individual models can exhibit significant biases in some subregions and seasons. The multimodel average generally outperforms any individual simulation, showing biases of similar magnitude to differences across a number of observational datasets. Moreover, many of the RCMs significantly improve the precipitation climate compared to that from their boundary condition dataset, that is, ERA-Interim. A common problem in the majority of the RCMs is that precipitation is triggered too early during the diurnal cycle, although a small subset of models does have a reasonable representation of the phase of the diurnal cycle. The systematic bias in the diurnal cycle is not improved when the ensemble mean is considered. Based on this performance analysis, it is assessed that the present set of RCMs can be used to provide useful information on climate projections over Africa.

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Climate Projections for South America: RegCM3 Driven by HadCM3 and ECHAM5

Advances in Meteorology ◽

10.1155/2014/376738 ◽

2014 ◽

Vol 2014 ◽

pp. 1-17 ◽

Cited By ~ 22

Author(s):

Michelle Simões Reboita ◽

Rosmeri Porfírio da Rocha ◽

Cássia Gabriele Dias ◽

Rita Yuri Ynoue

Keyword(s):

South America ◽

Climate Model ◽

Regional Climate ◽

Climate Projections ◽

South American ◽

Intergovernmental Panel ◽

Temperature And Precipitation ◽

Precipitation Increase ◽

Near Future ◽

Far Future

This study shows climate projections of air temperature and precipitation over South America (SA) from the Regional Climate Model version 3 (RegCM3) nested in ECHAM5 and HadCM3 global models. The projections consider the A1B scenario from Intergovernmental Panel on Climate Change (IPCC) and three time-slices: present (1960–1990), near- (2010–2040), and far-future (2070–2100) climates. In the future, RegCM3 projections indicate general warming throughout all SA and seasons, which is more pronounced in the far-future period. In this late period the RegCM3 projections indicate that the negative trend of precipitation over northern SA is also higher. In addition, a precipitation increase over southeastern SA is projected, mainly during summer and spring. The lifecycle of the South American monsoon (SAM) was also investigated in the present and future climates. In the near-future, the projections show a slight delay (one pentad) of the beginning of the rainy season, resulting in a small reduction of the SAM length. In the far-future, there is no agreement between projections related to the SAM features.

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Regional surface temperature simulations over the Iberian Peninsula: evaluation and climate projections

Climate Dynamics ◽

10.1007/s00382-020-05456-3 ◽

2020 ◽

Vol 55 (11-12) ◽

pp. 3445-3468

Author(s):

J. L. Garrido ◽

J. F. González-Rouco ◽

M. G. Vivanco ◽

J. Navarro

Keyword(s):

Iberian Peninsula ◽

21St Century ◽

Spatial Representation ◽

Climate Model ◽

Regional Climate ◽

Wrf Model ◽

Added Value ◽

Maximum Temperature ◽

Climate Projections ◽

Specific Configuration

Abstract The realism of a specific configuration of the WRF Regional Climate Model (RCM) to represent the observed temperature evolution over the Iberian Peninsula (IP) in the 1971–2005 period has been analyzed. The E-OBS observational dataset was used for this purpose. Also, the $$\textit{added value}$$ added value of the WRF simulations with respect to the IPSL Earth System Model (ESM) used to drive the WRF RCM was evaluated. In general, WRF presents lower temperatures than in the observations (negative biases) over the IP. These biases are comparatively larger than those of the driving ESM. Once the biases are corrected, WRF provides an added value in terms of a higher spatial representation. WRF introduces more variability in some regions in comparison to gridded observation. Warming trends according to the observations are also well represented by the RCM. In the second part of this study, the projections of future climate performed with both the ESM and the RCM were evaluated for the RCP4.5 and RCP8.5 scenarios during the 21st century. Although both models simulate temperature increases, the RCM simulates a smaller warming than the ESM after the mid-21st century, except for winter. Using the WRF model, the maximum temperature increase reaches $$6\, ^\circ \hbox {C}$$ 6 ∘ C and $$3\, ^\circ \hbox {C}$$ 3 ∘ C for RCP8.5 and RCP4.5 in the south east of the Iberian Peninsula by the end of the 21st century, respectively.

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Realised added value in dynamical downscaling of Australian climate change

10.5194/egusphere-egu21-3855 ◽

2021 ◽

Author(s):

Giovanni Di Virgilio ◽

Jason P. Evans ◽

Alejandro Di Luca ◽

Michael R. Grose ◽

Vanessa Round ◽

...

Keyword(s):

Climate Change ◽

Climate Models ◽

Climate Adaptation ◽

Regional Climate ◽

Future Climate ◽

Added Value ◽

Climate Projections ◽

Eastern Australia ◽

Australian Alps ◽

Future Climate Projections

<p>Coarse resolution global climate models (GCM) cannot resolve fine-scale drivers of regional climate, which is the scale where climate adaptation decisions are made. Regional climate models (RCMs) generate high-resolution projections by dynamically downscaling GCM outputs. However, evidence of where and when downscaling provides new information about both the current climate (added value, AV) and projected climate change signals, relative to driving data, is lacking. Seasons and locations where CORDEX-Australasia ERA-Interim and GCM-driven RCMs show AV for mean and extreme precipitation and temperature are identified. A new concept is introduced, &#8216;realised added value&#8217;, that identifies where and when RCMs simultaneously add value in the present climate and project a different climate change signal, thus suggesting plausible improvements in future climate projections by RCMs. ERA-Interim-driven RCMs add value to the simulation of summer-time mean precipitation, especially over northern and eastern Australia. GCM-driven RCMs show AV for precipitation over complex orography in south-eastern Australia during winter and widespread AV for mean and extreme minimum temperature during both seasons, especially over coastal and high-altitude areas. RCM projections of decreased winter rainfall over the Australian Alps and decreased summer rainfall over northern Australia are collocated with notable realised added value. Realised added value averaged across models, variables, seasons and statistics is evident across the majority of Australia and shows where plausible improvements in future climate projections are conferred by RCMs. This assessment of varying RCM capabilities to provide realised added value to GCM projections can be applied globally to inform climate adaptation and model development.</p>

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Assimilation of Lightning Data Using a Nudging Method Involving Low-Level Warming

Monthly Weather Review ◽

10.1175/mwr-d-14-00076.1 ◽

2014 ◽

Vol 142 (12) ◽

pp. 4850-4871 ◽

Cited By ~ 20

Author(s):

Max R. Marchand ◽

Henry E. Fuelberg

Keyword(s):

Numerical Models ◽

Deep Convection ◽

Computational Cost ◽

Wrf Model ◽

Stage Iv ◽

Simulated Precipitation ◽

Synoptic Forcing ◽

Total Lightning ◽

Mu Method ◽

Short Time

Abstract This study presents a new method for assimilating lightning data into numerical models that is suitable at convection-permitting scales. The authors utilized data from the Earth Networks Total Lightning Network at 9-km grid spacing to mimic the resolution of the Geostationary Lightning Mapper (GLM) that will be on the Geostationary Operational Environmental Satellite-R (GOES-R). The assimilation procedure utilizes the numerical Weather Research and Forecasting (WRF) Model. The method (denoted MU) warms the most unstable low levels of the atmosphere at locations where lightning was observed but deep convection was not simulated based on the absence of graupel. Simulation results are compared with those from a control simulation and a simulation employing the lightning assimilation method developed by Fierro et al. (denoted FO) that increases water vapor according to a nudging function that depends on the observed flash rate and simulated graupel mixing ratio. Results are presented for three severe storm days during 2011 and compared with hourly NCEP stage-IV precipitation observations. Compared to control simulations, both the MU and FO assimilation methods produce improved simulated precipitation fields during the assimilation period and a short time afterward based on subjective comparisons and objective statistical scores (~0.1, or 50%, improvement of equitable threat scores). The MU generally performs better at simulating isolated thunderstorms and other weakly forced deep convection, while FO performs better for the case having strong synoptic forcing. Results show that the newly developed MU method is a viable alternative to the FO method, exhibiting utility in producing thunderstorms where observed, and providing improved analyses at low computational cost.

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Precipitation over southern Africa: Is there consensus among GCMs, RCMs and observational data?

10.5194/gmd-2021-54 ◽

2021 ◽

Author(s):

Maria Chara Karypidou ◽

Eleni Katragkou ◽

Stefan Pieter Sobolowski

Keyword(s):

Climate Change ◽

Southern Africa ◽

Regional Climate ◽

Coupled Model ◽

Added Value ◽

Rain Gauges ◽

Climate Simulations ◽

Observational Uncertainty ◽

Direct Contrast ◽

Improved Performance

Abstract. The region of southern Africa (SAF) is highly vulnerable to the impacts of climate change and is projected to experience severe precipitation shortages in the coming decades. Ensuring that our modelling tools are fit for the purpose of assessing these changes is critical. In this work we compare a range of satellite products along with gauge-based datasets. Additionally, we investigate the behaviour of regional climate simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX) – Africa domain, along with simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6). We identify considerable variability in the standard deviation of precipitation between satellite products that merge with rain gauges and satellite products that do not, during the rainy season (Oct–Mar), indicating high observational uncertainty for specific regions over SAF. Good agreement both in spatial pattern and the strength of the calculated trends is found between satellite and gauge-based products, however. Both CORDEX-Africa and CMIP5 ensembles underestimate the observed trends during the analysis period. The CMIP6 ensemble displayed persistent drying trends, in direct contrast to the observations. The regional ensemble exhibited improved performance compared to its forcing (CMIP5), when the annual cycle and the extreme precipitation indices were examined, confirming the added value of the higher resolution regional climate simulations. The CMIP6 ensemble displayed a similar behaviour to CMIP5, however reducing slightly the ensemble spread. However, we show that reproduction of some key SAF phenomena, like the Angolan Low (which exerts a strong influence on regional precipitation), still poses a challenge for the global and regional models. This is likely a result of the complex climatic process that take place. Improvements in observational networks (both in-situ and satellite), as well as continued advancements in high-resolution modelling will be critical, in order to develop a robust assessment of climate change for southern Africa.

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The impact of RCM formulation and resolution on simulated precipitation in Africa

10.5194/esd-2019-55 ◽

2019 ◽

Cited By ~ 2

Author(s):

Minchao Wu ◽

Grigory Nikulin ◽

Erik Kjellström ◽

Danijel Belušić ◽

Colin Jones ◽

...

Keyword(s):

Climate Models ◽

Regional Climate ◽

Regional Climate Models ◽

Horizontal Resolution ◽

Added Value ◽

Primary Control ◽

Model Formulation ◽

Simulated Precipitation ◽

Mean Climate ◽

The Impact

Abstract. We investigate the impact of model formulation and horizontal resolution on the ability of Regional Climate Models (RCMs) to simulate precipitation in Africa. Two RCMs – SMHI-RCA4 and HCLIM38-ALADIN are utilized for downscaling the ERA-Interim reanalysis over Africa at four different resolutions: 25, 50, 100 and 200 km. Additionally to the two RCMs, two different configurations of the same RCA4 are used. Contrasting different RCMs, configurations and resolutions it is found that model formulation has the primary control over many aspects of the precipitation climatology in Africa. Patterns of spatial biases in seasonal mean precipitation are mostly defined by model formulation while the magnitude of the biases is controlled by resolution. In a similar way, the phase of the diurnal cycle is completely controlled by model formulation (convection scheme) while its amplitude is a function of resolution. Although higher resolution in many cases leads to smaller biases in the time mean climate, the impact of higher resolution is mixed. An improvement in one region/season (e.g. reduction of dry biases) often corresponds to a deterioration in another region/season (e.g. amplification of wet biases). The experiments confirm a pronounced and well known impact of higher resolution – a more realistic distribution of daily precipitation. Even if the time-mean climate is not always greatly sensitive to resolution, what the time-mean climate is made up of, higher order statistics, is sensitive. Therefore, the realism of the simulated precipitation increases as resolution increases. Our results show that improvements in the ability of RCMs to simulate precipitation in Africa compared to their driving reanalysis in many cases are simply related to model formulation and not necessarily to higher resolution. Such model formulation related improvements are strongly model dependent and in general cannot be considered as an added value of downscaling.

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Multidecadal Evaluation of WRF Downscaling Capabilities over Western Australia in Simulating Rainfall and Temperature Extremes

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-14-0212.1 ◽

2015 ◽

Vol 54 (2) ◽

pp. 370-394 ◽

Cited By ~ 17

Author(s):

Julia Andrys ◽

Thomas J. Lyons ◽

Jatin Kala

Keyword(s):

High Resolution ◽

Western Australia ◽

General Circulation ◽

Regional Climate ◽

Wrf Model ◽

Climate Extremes ◽

Convective Precipitation ◽

Climate Simulation ◽

Climate Indices ◽

Climate Simulations

AbstractThe authors evaluate a 30-yr (1981–2010) Weather Research and Forecast (WRF) Model regional climate simulation over the southwest of Western Australia (SWWA), a region with a Mediterranean climate, using ERA-Interim boundary conditions. The analysis assesses the spatial and temporal characteristics of climate extremes, using a selection of climate indices, with an emphasis on metrics that are relevant for forestry and agricultural applications. Two nested domains at 10- and 5-km resolution are examined, with the higher-resolution simulation resolving convection explicitly. Simulation results are compared with a high-resolution, gridded observational dataset that provides daily rainfall, minimum temperatures, and maximum temperatures. Results show that, at both resolutions, the model is able to simulate the daily, seasonal, and annual variation of temperature and precipitation well, including extreme events. The higher-resolution domain displayed significant performance gains in simulating dry-season convective precipitation, rainfall around complex terrain, and the spatial distribution of frost conditions. The high-resolution domain was, however, influenced by grid-edge effects in the southwestern margin, which reduced the ability of the domain to represent frontal rainfall along the coastal region. On the basis of these results, the authors feel confident in using the WRF Model for regional climate simulations for the SWWA, including studies that focus on the spatial and temporal representation of climate extremes. This study provides a baseline climatological description at a high resolution that can be used for impact studies and will also provide a benchmark for climate simulations driven by general circulation models.

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