scholarly journals Integration of Lidar Data into a Coupled Mesoscale–Land Surface Model: A Theoretical Assessment of Sensitivity of Urban–Coastal Mesoscale Circulations to Urban Canopy Parameters

2012 ◽  
Vol 29 (3) ◽  
pp. 328-346 ◽  
Author(s):  
Michael Carter ◽  
J. Marshall Shepherd ◽  
Steve Burian ◽  
Indu Jeyachandran
Keyword(s):  
Urban Environment ◽  
Land Surface ◽  
Urban Canopy ◽  
Vertical Motion ◽  
Sea Breeze ◽  
Surface Model ◽  
Lidar Data ◽  
Mesoscale Circulations ◽  
The Impact ◽  
Urban Weather

Abstract Urban–coastal circulations affect urban weather, dispersion and transport of pollutants and contaminants, and climate. Proper characterization and prediction of thermodynamic and dynamic processes in such environments are warranted. A new generation of observation and modeling systems is enabling unprecedented characterization of the three-dimensionality of the urban environment, including morphological parameters. Urban areas of Houston, Texas, are classified according to lidar-measured building heights and assigned typical urban land surface parameters appropriate to each classification. The lidar data were degraded from 1 m to the model resolution (1 km) with the goal of evaluating the impact of degraded resolution urban canopy parameters (UCPs) and three-dimensionality on the coastal–urban mesoscale circulations in comparison to typical two-dimensional urban slab approaches. The study revealed complex interactions between the sea breeze and urban heat island and offers a novel diagnostic tool, the bulk Richardson shear number, for identifying shallow mesoscale circulation. Using the Advanced Research Weather Research and Forecasting model (ARW-WRF) coupled to an atmosphere–land surface–urban canopy model, the authors simulated a theoretical sea-breeze day and confirmed that while coastal morphology can itself lead to complex sea-breeze front structures, including preferred areas of vertical motion, the urban environment can have an impact on the evolution of the sea-breeze mesoscale boundary. The inclusion of lidar-derived UCPs, even at degraded resolution, in the model’s land surface representation can lead to significant differences in patterns of skin surface temperature, convergence, and vertical motion, which have implications for many aspects of urban weather.

scholarly journals Impact of urban canopy meteorological forcing on aerosol concentrations

2018 ◽  
Author(s):  
Peter Huszar ◽  
Michal Belda ◽  
Jan Karlický ◽  
Tatsiana Bardachova ◽  
Tomas Halenka ◽  
...  
Keyword(s):  
Land Surface ◽  
Urban Areas ◽  
Urban Canopy ◽  
Specific Humidity ◽  
Surface Model ◽  
Meteorological Forcing ◽  
Turbulent Diffusion Coefficient ◽  
Temperature Impact ◽  
The Impact ◽  
Meteorological Effects

Abstract. The regional climate model RegCM4 extended with the land-surface model CLM4.5 was coupled to the chemistry transport model CAMx to analyze the impact of urban meteorological forcing on the surface fine aerosol (PM2.5) concentrations for summer conditions over the 2001–2005 period focusing on the area of Europe. Starting with the analysis of the meteorological modifications caused by urban canopy forcing we found significant increases of urban surface temperatures (up to 2–3 K), decrease of specific humidity (by up to 0.4–0.6 g/kg) reduction of wind speed (up to −1 m/s) and enhancement of vertical turbulent diffusion coefficient (up to 60–70 m2/s). These modifications translated into significant changes in surface aerosol concentrations that were calculated by cascading experimental approach. First, none of the urban meteorological effects were considered. Than, the temperature effect was added, than the humidity, the wind and finally, the enhanced turbulence was considered in the chemical runs. This facilitated the understanding of the underlying processes acting to modify urban aerosol concentrations. Moreover, we looked at the impact of the individual aerosol components as well. The urban induced temperature changes resulted in decreases of PM2.5 by −1.5 to −2 μg/m3, while decreased urban winds resulted in increases by 1–2 μg/m3. The enhanced turbulence over urban areas results in decreases of PM2.5 by −2 μg/m3. The combined effect of all individual impact depends on the competition between the partial impacts and can reach up to −3 μg/m3 for some cities, especially were the temperature impact was stronger in magnitude than the wind impact. The effect of changed humidity was found to be minor. The main contributor to the temperature impact is the modification of secondary inorganic aerosols, mainly nitrates, while the wind and turbulence impact is most pronounced in case of primary aerosol (primary black and organic carbon and other fine particle matter). The overall as well as individual impacts on secondary organic aerosol is very small with the increased turbulence acting as the main driver. The analysis of the vertical extend of the aerosol changes showed that the perturbations caused by urban canopy forcing, besides being large near the surface, have a secondary maximum for turbulence and wind impact over higher model levels, which is attributed to the vertical extend of the changes in turbulence over urban areas. The validation of model data with measurements showed good agreement and we could detect a clear model improvement at some areas when including the urban canopy meteorological effects in our chemistry simulations.

scholarly journals Impact of an improved WRF urban canopy model on diurnal air temperature simulation over northern Taiwan

2016 ◽  
Vol 16 (3) ◽  
pp. 1809-1822 ◽  
Author(s):  
Chuan-Yao Lin ◽  
Chiung-Jui Su ◽  
Hiroyuki Kusaka ◽  
Yuko Akimoto ◽  
Yang-Fan Sheng ◽  
...  
Keyword(s):  
Land Surface ◽  
Urban Areas ◽  
Urban Canopy ◽  
Anthropogenic Heat ◽  
Surface Model ◽  
Urban Canopy Model ◽  
Simulation Performance ◽  
The Impact ◽  
Canopy Model ◽  
Northern Taiwan

Abstract. This study evaluates the impact of urbanization over northern Taiwan using the Weather Research and Forecasting (WRF) Model coupled with the Noah land-surface model and a modified urban canopy model (WRF–UCM2D). In the original UCM coupled to WRF (WRF–UCM), when the land use in the model grid is identified as "urban", the urban fraction value is fixed. Similarly, the UCM assumes the distribution of anthropogenic heat (AH) to be constant. This may not only lead to over- or underestimation of urban fraction and AH in urban and non-urban areas, but spatial variation also affects the model-estimated temperature. To overcome the abovementioned limitations and to improve the performance of the original UCM model, WRF–UCM is modified to consider the 2-D urban fraction and AH (WRF–UCM2D).The two models were found to have comparable temperature simulation performance for urban areas, but large differences in simulated results were observed for non-urban areas, especially at nighttime. WRF–UCM2D yielded a higher correlation coefficient (R2) than WRF–UCM (0.72 vs. 0.48, respectively), while bias and RMSE achieved by WRF–UCM2D were both significantly smaller than those attained by WRF–UCM (0.27 and 1.27 vs. 1.12 and 1.89, respectively). In other words, the improved model not only enhanced correlation but also reduced bias and RMSE for the nighttime data of non-urban areas. WRF–UCM2D performed much better than WRF–UCM at non-urban stations with a low urban fraction during nighttime. The improved simulation performance of WRF–UCM2D in non-urban areas is attributed to the energy exchange which enables efficient turbulence mixing at a low urban fraction. The result of this study has a crucial implication for assessing the impacts of urbanization on air quality and regional climate.

scholarly journals Impact of an improved WRF-urban canopy model on diurnal air temperature simulation over northern Taiwan

2015 ◽  
Vol 15 (20) ◽  
pp. 28483-28516
Author(s):  
C.-Y. Lin ◽  
C.-J. Su ◽  
H. Kusaka ◽  
Y. Akimoto ◽  
Y. F. Sheng ◽  
...  
Keyword(s):  
Land Surface ◽  
Urban Areas ◽  
Urban Canopy ◽  
Anthropogenic Heat ◽  
Surface Model ◽  
Urban Canopy Model ◽  
Simulation Performance ◽  
The Impact ◽  
Canopy Model ◽  
Northern Taiwan

Abstract. This study evaluated the impact of urbanization over northern Taiwan using the Weather Research and Forecasting (WRF) model coupled with the Noah land-surface model and a modified Urban Canopy Model (WRF-UCM2D). In the original UCM coupled in WRF (WRF-UCM), when the land use in the model grid net is identified as "urban", the urban fraction value is fixed. Similarly, the UCM assumes the distribution of anthropogenic heat (AH) to be constant. Such not only may lead to over- or underestimation, the temperature difference between urban and non-urban areas has also been neglected. To overcome the above-mentioned limitations and to improve the performance of the original UCM model, WRF-UCM is modified to consider the 2-D urban fraction and AH (WRF-UCM2D). The two models were found to have comparable simulation performance for urban areas but large differences in simulated results were observed for non-urban, especially at nighttime. WRF-UCM2D yielded a higher R2 than WRF-UCM (0.72 vs. 0.48, respectively), while bias and RMSE achieved by WRF-UCM2D were both significantly smaller than those attained by WRF-UCM (0.27 and 1.27 vs. 1.12 and 1.89, respectively). In other words, the improved model not only enhanced correlation but also reduced bias and RMSE for the nighttime data of non-urban areas. WRF-UCM2D performed much better than WRF-UCM at non-urban stations with low urban fraction during nighttime. The improved simulation performance of WRF-UCM2D at non-urban area is attributed to the energy exchange which enables efficient turbulence mixing at low urban fraction. The achievement of this study has a crucial implication for assessing the impacts of urbanization on air quality and regional climate.

scholarly journals Influence of Land Cover and Soil Moisture on the Horizontal Distribution of Sensible and Latent Heat Fluxes in Southeast Kansas during IHOP_2002 and CASES-97

2007 ◽  
Vol 8 (1) ◽  
pp. 68-87 ◽  
Author(s):  
Margaret A. LeMone ◽  
Fei Chen ◽  
Joseph G. Alfieri ◽  
Mukul Tewari ◽  
Bart Geerts ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Latent Heat ◽  
Land Surface ◽  
Field Experiments ◽  
Time Of Day ◽  
Horizontal Distribution ◽  
Heat Fluxes ◽  
Surface Model ◽  
Green Vegetation ◽  
The Impact

Abstract Analyses of daytime fair-weather aircraft and surface-flux tower data from the May–June 2002 International H2O Project (IHOP_2002) and the April–May 1997 Cooperative Atmosphere Surface Exchange Study (CASES-97) are used to document the role of vegetation, soil moisture, and terrain in determining the horizontal variability of latent heat LE and sensible heat H along a 46-km flight track in southeast Kansas. Combining the two field experiments clearly reveals the strong influence of vegetation cover, with H maxima over sparse/dormant vegetation, and H minima over green vegetation; and, to a lesser extent, LE maxima over green vegetation, and LE minima over sparse/dormant vegetation. If the small number of cases is producing the correct trend, other effects of vegetation and the impact of soil moisture emerge through examining the slope ΔxyLE/ΔxyH for the best-fit straight line for plots of time-averaged LE as a function of time-averaged H over the area. Based on the surface energy balance, H + LE = Rnet − Gsfc, where Rnet is the net radiation and Gsfc is the flux into the soil; Rnet − Gsfc ∼ constant over the area implies an approximately −1 slope. Right after rainfall, H and LE vary too little horizontally to define a slope. After sufficient drying to produce enough horizontal variation to define a slope, a steep (∼−2) slope emerges. The slope becomes shallower and better defined with time as H and LE horizontal variability increases. Similarly, the slope becomes more negative with moister soils. In addition, the slope can change with time of day due to phase differences in H and LE. These trends are based on land surface model (LSM) runs and observations collected under nearly clear skies; the vegetation is unstressed for the days examined. LSM runs suggest terrain may also play a role, but observational support is weak.

scholarly journals Coupling a land-surface model with a crop growth model to improve ET flux estimations in the Upper Ganges basin, India

2014 ◽  
Vol 18 (10) ◽  
pp. 4223-4238 ◽  
Author(s):  
G. M. Tsarouchi ◽  
W. Buytaert ◽  
A. Mijic
Keyword(s):  
Growth Model ◽  
Land Surface ◽  
Coupled Model ◽  
Crop Growth ◽  
Original Model ◽  
Surface Model ◽  
Strong Impact ◽  
Crop Growth Model ◽  
Mean Error ◽  
The Impact

Abstract. Land-Surface Models (LSMs) are tools that represent energy and water flux exchanges between land and the atmosphere. Although much progress has been made in adding detailed physical processes into these models, there is much room left for improved estimates of evapotranspiration fluxes, by including a more reasonable and accurate representation of crop dynamics. Recent studies suggest a strong land-surface–atmosphere coupling over India and since this is one of the most intensively cultivated areas in the world, the strong impact of crops on the evaporative flux cannot be neglected. In this study we dynamically couple the LSM JULES with the crop growth model InfoCrop. JULES in its current version (v3.4) does not simulate crop growth. Instead, it treats crops as natural grass, while using prescribed vegetation parameters. Such simplification might lead to modelling errors. Therefore we developed a coupled modelling scheme that simulates dynamically crop development and parametrized it for the two main crops of the study area, wheat and rice. This setup is used to examine the impact of inter-seasonal land cover changes in evapotranspiration fluxes of the Upper Ganges River basin (India). The sensitivity of JULES with regard to the dynamics of the vegetation cover is evaluated. Our results show that the model is sensitive to the changes introduced after coupling it with the crop model. Evapotranspiration fluxes, which are significantly different between the original and the coupled model, are giving an approximation of the magnitude of error to be expected in LSMs that do not include dynamic crop growth. For the wet season, in the original model, the monthly Mean Error ranges from 7.5 to 24.4 mm month−1, depending on different precipitation forcing. For the same season, in the coupled model, the monthly Mean Error's range is reduced to 5.4–11.6 mm month−1. For the dry season, in the original model, the monthly Mean Error ranges from 10 to 17 mm month−1, depending on different precipitation forcing. For the same season, in the coupled model, the monthly Mean Error's range is reduced to 2.2–3.4 mm month−1. The new modelling scheme, by offering increased accuracy of evapotranspiration estimations, is an important step towards a better understanding of the two-way crops–atmosphere interactions.

scholarly journals Continuous high-resolution midlatitude-belt simulations for July–August 2013 with WRF

2017 ◽  
Vol 10 (5) ◽  
pp. 2031-2055 ◽  
Author(s):  
Thomas Schwitalla ◽  
Hans-Stefan Bauer ◽  
Volker Wulfmeyer ◽  
Kirsten Warrach-Sagi
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Large Scale ◽  
Temperature Fields ◽  
Surface Model ◽  
Limited Area ◽  
Data Set ◽  
Latitude Belt ◽  
Simulated Precipitation ◽  
The Impact

Abstract. Increasing computational resources and the demands of impact modelers, stake holders, and society envision seasonal and climate simulations with the convection-permitting resolution. So far such a resolution is only achieved with a limited-area model whose results are impacted by zonal and meridional boundaries. Here, we present the setup of a latitude-belt domain that reduces disturbances originating from the western and eastern boundaries and therefore allows for studying the impact of model resolution and physical parameterization. The Weather Research and Forecasting (WRF) model coupled to the NOAH land–surface model was operated during July and August 2013 at two different horizontal resolutions, namely 0.03 (HIRES) and 0.12° (LOWRES). Both simulations were forced by the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis data at the northern and southern domain boundaries, and the high-resolution Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) data at the sea surface.The simulations are compared to the operational ECMWF analysis for the representation of large-scale features. To analyze the simulated precipitation, the operational ECMWF forecast, the CPC MORPHing (CMORPH), and the ENSEMBLES gridded observation precipitation data set (E-OBS) were used as references.Analyzing pressure, geopotential height, wind, and temperature fields as well as precipitation revealed (1) a benefit from the higher resolution concerning the reduction of monthly biases, root mean square error, and an improved Pearson skill score, and (2) deficiencies in the physical parameterizations leading to notable biases in distinct regions like the polar Atlantic for the LOWRES simulation, the North Pacific, and Inner Mongolia for both resolutions.In summary, the application of a latitude belt on a convection-permitting resolution shows promising results that are beneficial for future seasonal forecasting.

scholarly journals The Impact of Error Accounting in a Bayesian Approach to Calibrating Modeled Turbulent Fluxes in an Open-Canopy Forest

2017 ◽  
Vol 18 (7) ◽  
pp. 2029-2042
Author(s):  
Tony E. Wong ◽  
William Kleiber ◽  
David C. Noone
Keyword(s):  
Markov Chain ◽  
Land Surface ◽  
Hydrological Modeling ◽  
Soil Layer ◽  
Turbulent Fluxes ◽  
Surface Model ◽  
Model Parameters ◽  
Top Soil ◽  
The Impact ◽  
Calibration Approach

Abstract Land surface models are notorious for containing many parameters that control the exchange of heat and moisture between land and atmosphere. Properly modeling the partitioning of total evapotranspiration (ET) between transpiration and evaporation is critical for accurate hydrological modeling, but depends heavily on the treatment of turbulence within and above canopies. Previous work has constrained estimates of evapotranspiration and its partitioning using statistical approaches that calibrate land surface model parameters by assimilating in situ measurements. These studies, however, are silent on the impacts of the accounting of uncertainty within the statistical calibration framework. The present study calibrates the aerodynamic, leaf boundary layer, and stomatal resistance parameters, which partially control canopy turbulent exchange and thus the evapotranspiration flux partitioning. Using an adaptive Metropolis–Hastings algorithm to construct a Markov chain of draws from the joint posterior distribution of these resistance parameters, an ensemble of model realizations is generated, in which latent and sensible heat fluxes and top soil layer temperature are optimized. A set of five calibration experiments demonstrate that model performance is sensitive to the accounting of various sources of uncertainty in the field observations and model output and that it is critical to account for model structural uncertainty. After calibration, the modeled fluxes and top soil layer temperature are largely free from bias, and this calibration approach successfully informs and characterizes uncertainty in these parameters, which is essential for model improvement and development. The key points of this paper are 1) a Markov chain Monte Carlo calibration approach successfully improves modeled turbulent fluxes; 2) ET partitioning estimates hinge on the representation of uncertainties in the model and data; and 3) despite these inherent uncertainties, constrained posterior estimates of ET partitioning emerge.

scholarly journals Development and application of the WRFPLUS-Chem online chemistry adjoint and WRFDA-Chem assimilation system

2015 ◽  
Vol 8 (6) ◽  
pp. 1857-1876 ◽  
Author(s):  
J. J. Guerrette ◽  
D. K. Henze
Keyword(s):  
Land Surface ◽  
Vertical Mixing ◽  
Model Performance ◽  
Land Surface Model ◽  
Sensitivity Study ◽  
Climate Impacts ◽  
Surface Model ◽  
Time Period ◽  
Develop Land ◽  
The Impact

Abstract. Here we present the online meteorology and chemistry adjoint and tangent linear model, WRFPLUS-Chem (Weather Research and Forecasting plus chemistry), which incorporates modules to treat boundary layer mixing, emission, aging, dry deposition, and advection of black carbon aerosol. We also develop land surface and surface layer adjoints to account for coupling between radiation and vertical mixing. Model performance is verified against finite difference derivative approximations. A second-order checkpointing scheme is created to reduce computational costs and enable simulations longer than 6 h. The adjoint is coupled to WRFDA-Chem, in order to conduct a sensitivity study of anthropogenic and biomass burning sources throughout California during the 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field campaign. A cost-function weighting scheme was devised to reduce the impact of statistically insignificant residual errors in future inverse modeling studies. Results of the sensitivity study show that, for this domain and time period, anthropogenic emissions are overpredicted, while wildfire emission error signs vary spatially. We consider the diurnal variation in emission sensitivities to determine at what time sources should be scaled up or down. Also, adjoint sensitivities for two choices of land surface model (LSM) indicate that emission inversion results would be sensitive to forward model configuration. The tools described here are the first step in conducting four-dimensional variational data assimilation in a coupled meteorology–chemistry model, which will potentially provide new constraints on aerosol precursor emissions and their distributions. Such analyses will be invaluable to assessments of particulate matter health and climate impacts.

scholarly journals High-resolution fully-coupled atmospheric–hydrological modeling: a cross-compartment regional water and energy cycle evaluation

2020 ◽  
Author(s):  
Benjamin Fersch ◽  
Alfonso Senatore ◽  
Bianca Adler ◽  
Joël Arnault ◽  
Matthias Mauder ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Land Surface ◽  
Hydrological Modeling ◽  
Weather Prediction ◽  
Surface Model ◽  
Near Surface ◽  
Ground Heat Flux ◽  
The Impact ◽  
Fully Coupled ◽  
Regional Water

<p>The land surface and the atmospheric boundary layer are closely intertwined with respect to the exchange of water, trace gases and energy. Nonlinear feedback and scale dependent mechanisms are obvious by observations and theories. Modeling instead is often narrowed to single compartments of the terrestrial system or bound to traditional viewpoints of definite scientific disciplines. Coupled terrestrial hydrometeorological modeling systems attempt to overcome these limitations to achieve a better integration of the processes relevant for regional climate studies and local area weather prediction. We examine the ability of the hydrologically enhanced version of the Weather Research and Forecasting Model (WRF-Hydro) to reproduce the regional water cycle by means of a two-way coupled approach and assess the impact of hydrological coupling with respect to a traditional regional atmospheric model setting. It includes the observation-based calibration of the hydrological model component (offline WRF-Hydro) and a comparison of the classic WRF and the fully coupled WRF-Hydro models both with identical calibrated parameter settings for the land surface model (Noah-MP). The simulations are evaluated based on extensive observations at the pre-Alpine Terrestrial Environmental Observatory (TERENO Pre-Alpine) for the Ammer (600 km²) and Rott (55 km²) river catchments in southern Germany, covering a five month period (Jun–Oct 2016).</p><p>The sensitivity of 7 land surface parameters is tested using the <em>Latin-Hypercube One-factor-At-a-Time</em> (LH-OAT) method and 6 sensitive parameters are subsequently optimized for 6 different subcatchments, using the Model-Independent <em>Parameter Estimation and Uncertainty Analysis software</em> (PEST).</p><p>The calibration of the offline WRF-Hydro leads to Nash-Sutcliffe efficiencies between 0.56 and 0.64 and volumetric efficiencies between 0.46 and 0.81 for the six subcatchments. The comparison of classic WRF and fully coupled WRF-Hydro shows only tiny alterations for radiation and precipitation but considerable changes for moisture- and energy fluxes. By comparison with TERENO Pre-Alpine observations, the fully coupled model slightly outperforms the classic WRF with respect to evapotranspiration, sensible and ground heat flux, near surface mixing ratio, temperature, and boundary layer profiles of air temperature. The subcatchment-based water budgets show uniformly directed variations for evapotranspiration, infiltration excess and percolation whereas soil moisture and precipitation change randomly.</p>

scholarly journals Exploring how groundwater buffers the influence of heatwaves on vegetation function during multi-year droughts

2021 ◽  
Vol 12 (3) ◽  
pp. 919-938
Author(s):  
Mengyuan Mu ◽  
Martin G. De Kauwe ◽  
Anna M. Ukkola ◽  
Andy J. Pitman ◽  
Weidong Guo ◽  
...  
Keyword(s):  
Land Surface ◽  
Forest Canopy ◽  
Climate Models ◽  
Root Zone ◽  
Stomatal Closure ◽  
Capillary Rise ◽  
Vapour Pressure Deficit ◽  
Global Climate Models ◽  
Surface Model ◽  
The Impact

Abstract. The co-occurrence of droughts and heatwaves can have significant impacts on many socioeconomic and environmental systems. Groundwater has the potential to moderate the impact of droughts and heatwaves by moistening the soil and enabling vegetation to maintain higher evaporation, thereby cooling the canopy. We use the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model, coupled to a groundwater scheme, to examine how groundwater influences ecosystems under conditions of co-occurring droughts and heatwaves. We focus specifically on south-east Australia for the period 2000–2019, when two significant droughts and multiple extreme heatwave events occurred. We found groundwater plays an important role in helping vegetation maintain transpiration, particularly in the first 1–2 years of a multi-year drought. Groundwater impedes gravity-driven drainage and moistens the root zone via capillary rise. These mechanisms reduced forest canopy temperatures by up to 5 ∘C during individual heatwaves, particularly where the water table depth is shallow. The role of groundwater diminishes as the drought lengthens beyond 2 years and soil water reserves are depleted. Further, the lack of deep roots or stomatal closure caused by high vapour pressure deficit or high temperatures can reduce the additional transpiration induced by groundwater. The capacity of groundwater to moderate both water and heat stress on ecosystems during simultaneous droughts and heatwaves is not represented in most global climate models, suggesting that model projections may overestimate the risk of these events in the future.

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