scholarly journals Review for gmd-2020-86: “Land Surface Model influence on the simulated climatologies of temperature and precipitation extremes in the WRF v.3.9 model over North America” by García-García et al.

2020 ◽  
Keyword(s):  
North America ◽  
Land Surface ◽  
Land Surface Model ◽  
Precipitation Extremes ◽  
Surface Model ◽  
Temperature And Precipitation

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.

scholarly journals Assessment of WRF Land Surface Model Performance over West Africa

2020 ◽  
Vol 2020 ◽  
pp. 1-30
Author(s):  
Ifeanyi C. Achugbu ◽  
Jimy Dudhia ◽  
Ayorinde A. Olufayo ◽  
Ifeoluwa A. Balogun ◽  
Elijah A. Adefisan ◽  
...  
Keyword(s):  
West Africa ◽  
Land Surface ◽  
Model Performance ◽  
Wrf Model ◽  
Land Surface Model ◽  
Surface Model ◽  
Reanalysis Dataset ◽  
The North ◽  
Temperature And Precipitation ◽  
Moisture Advection

Simulations with four land surface models (LSMs) (i.e., Noah, Noah-MP, Noah-MP with ground water GW option, and CLM4) using the Weather Research and Forecasting (WRF) model at 12 km horizontal grid resolution were carried out as two sets for 3 months (December–February 2011/2012 and July–September 2012) over West Africa. The objective is to assess the performance of WRF LSMs in simulating meteorological parameters over West Africa. The model precipitation was assessed against TRMM while surface temperature was compared with the ERA-Interim reanalysis dataset. Results show that the LSMs performed differently for different variables in different land-surface conditions. Based on precipitation and temperature, Noah-MP GW is overall the best for all the variables and seasons in combination, while Noah came last. Specifically, Noah-MP GW performed best for JAS temperature and precipitation; CLM4 was the best in simulating DJF precipitation, while Noah was the best in simulating DJF temperature. Noah-MP GW has the wettest Sahel while Noah has the driest one. The strength of the Tropical Easterly Jet (TEJ) is strongest in Noah-MP GW and Noah-MP compared with that in CLM4 and Noah. The core of the African Easterly Jet (AEJ) lies around 12°N in Noah and 15°N for Noah-MP GW. Noah-MP GW and Noah-MP simulations have stronger influx of moisture advection from the southwesterly monsoonal wind than the CLM4 and Noah with Noah showing the least influx. Also, analysis of the evaporative fraction shows sharp gradient for Noah-MP GW and Noah-MP with wetter Sahel further to the north and further to the south for Noah. Noah-MP-GW has the highest amount of soil moisture, while the CLM4 has the least for both the JAS and DJF seasons. The CLM4 has the highest LH for both DJF and JAS seasons but however has the least SH for both DJF and JAS seasons. The principal difference between the LSMs is in the vegetation representation, description, and parameterization of the soil water column; hence, improvement is recommended in this regard.

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.

scholarly journals Methane fluxes in the high northern latitudes for 2005–2013 estimated using a Bayesian atmospheric inversion

2016 ◽  
Author(s):  
Rona L. Thompson ◽  
Motoki Sasakawa ◽  
Toshinobu Machida ◽  
Tuula Aalto ◽  
Doug Worthy ◽  
...  
Keyword(s):  
North America ◽  
Soil Temperature ◽  
Land Surface ◽  
Dispersion Model ◽  
Land Surface Model ◽  
Particle Dispersion ◽  
Anthropogenic Sources ◽  
Surface Model ◽  
Northern Latitudes ◽  
North Eurasia

Abstract. We present methane (CH4) flux estimates for 2005 to 2013 from a Bayesian inversion focusing on the high northern latitudes (north of 50° N). Our inversion is based on atmospheric transport modelled by the Lagrangian particle dispersion model, FLEXPART, and CH4 observations from 17 in-situ and 5 discrete flask-sampling sites distributed over northern North America and Eurasia. CH4 fluxes are determined at monthly temporal resolution and on a variable grid with maximum resolution of 1° × 1°. Our inversion finds a CH4 source from the high northern latitudes of 82 to 84 Tg y−1, constituting ~15 % of the global total, compared to 64 to 68 Tg y−1 (~12 %) in the prior estimates. For northern North America, we estimate a mean source of 16.6 to 17.9 Tg y−1, which is dominated by fluxes in the Hudson Bay Lowlands (HBL) and western Canada, specifically, the province of Alberta. Our estimate for the HBL, of 2.7 to 3.4 Tg y−1, is close to the prior estimate (which includes wetland fluxes from the land surface model, LPX-Bern) and to other independent inversion estimates. However, our estimate for Alberta, of 5.0 to 5.8 Tg y−1 is significantly higher than the prior (which also includes anthropogenic sources from the EDGAR-4.2FT2010 inventory). Since the fluxes from this region persist throughout the winter, this may signify that the anthropogenic emissions are underestimated. For North Eurasia, we find a mean source of 52.2 to 55.5 Tg y−1, with a strong contribution from fluxes in the Western Siberian Lowlands (WSL) for which we estimate a source of 19.3 to 19.9 Tg y−1. Over the 9-year inversion period, we find significant year-to-year variations in the fluxes, which in North America and, specifically, in the HBL appear to be driven at least in part by soil temperature, while in the WSL, the variability is more dependent on soil moisture. Moreover, we find significant positive trends in the CH4 fluxes in North America of 0.38 to 0.57 Tg y−1 per year, and North Eurasia of 0.76 to 1.09 Tg y−1 per year. In North America, this could be due to an increase in soil temperature, while in North Eurasia, specifically, Russia, the trend is likely due, at least in part, to an increase in anthropogenic sources.

scholarly journals Climate model based consensus on the hydrologic impacts of climate change to the Rio Lempa basin of Central America

2008 ◽  
Vol 5 (6) ◽  
pp. 3099-3128 ◽  
Author(s):  
E. P. Maurer ◽  
J. C. Adam ◽  
A. W. Wood
Keyword(s):  
Central America ◽  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Land Surface Model ◽  
Low Flow ◽  
Surface Model ◽  
Temperature And Precipitation ◽  
Hydrologic Impacts ◽  
Emissions Scenarios

Abstract. Temperature and precipitation from 16 climate models each using two emissions scenarios (lower B1 and mid-high A2) were used to characterize the range of potential climate changes for the Rio Lempa basin of Central America during the middle (2040–2069) and end (2070–2099) of the 21st century. A land surface model was applied to investigate the hydrologic impacts of these changes, focusing on inflow to two major hydropower reservoirs. By 2070–2099 the median warming relative to 1961–1990 was 1.9°C and 3.4°C under B1 and A2 emissions, respectively. For the same periods, the models project median precipitation decreases of 5.0% (B1) and 10.4% (A2). Median changes by 2070–2099 in reservoir inflow were 13% (B1) and 24% (A2), with largest flow reductions during the rising limb of the seasonal hydrograph, from June through September. Frequency of low flow years increases, implying decreases in firm hydropower capacity of 33% to 53% by 2070–2099.

scholarly journals Online dynamical downscaling of temperature and precipitation within the iLOVECLIM model (version 1.1)

2017 ◽  
Author(s):  
Aurélien Quiquet ◽  
Didier M. Roche ◽  
Christophe Dumas ◽  
Didier Paillard
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Large Scale ◽  
Dynamical Downscaling ◽  
Land Surface Model ◽  
Atmospheric Model ◽  
Scale Model ◽  
Surface Model ◽  
Model Parameters ◽  
Temperature And Precipitation

Abstract. In this paper, we present the inclusion of an online dynamical downscaling of heat and moisture within the model of intermediate complexity iLOVECLIM v1.1. We describe the followed methodology to generate temperature and precipitation fields on a 40 km × 40 km Cartesian grid of the Northern Hemisphere from the T21 native atmospheric model grid. Our scheme is non grid-specific and conserves energy and moisture. We show that we are able to generate a high resolution field which presents a spatial variability in better agreement with the observations compared to the standard model. Whilst the large-scale model biases are not corrected, for selected model parameters, the downscaling can induce a better overall performance compared to the standard version on both the high-resolution grid and on the native grid. Foreseen applications of this new model feature includes ice sheet model coupling and high-resolution land surface model.

scholarly journals Supplementary material to "WRF v.3.9 sensitivity to land surface model and horizontal resolution changes over North America"

2021 ◽  
Author(s):  
Almudena García-García ◽  
Francisco José Cuesta-Valero ◽  
Hugo Beltrami ◽  
Fidel González-Rouco ◽  
Elena García-Bustamante
Keyword(s):  
North America ◽  
Land Surface ◽  
Land Surface Model ◽  
Horizontal Resolution ◽  
Surface Model ◽  
Supplementary Material
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