scholarly journals Evaluation of urban surface parameterizations in the WRF model using measurements during the Texas Air Quality Study 2006 field campaign

2011 ◽  
Vol 11 (5) ◽  
pp. 2127-2143 ◽  
Author(s):  
S.-H. Lee ◽  
S.-W. Kim ◽  
W. M. Angevine ◽  
L. Bianco ◽  
S. A. McKeen ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Air Quality ◽  
Air Temperature ◽  
Urban Areas ◽  
Surface Air Temperature ◽  
Urban Vegetation ◽  
Galveston Bay ◽  
Near Surface ◽  
Field Campaign ◽  
Quality Study

Abstract. The performance of different urban surface parameterizations in the WRF (Weather Research and Forecasting) in simulating urban boundary layer (UBL) was investigated using extensive measurements during the Texas Air Quality Study 2006 field campaign. The extensive field measurements collected on surface (meteorological, wind profiler, energy balance flux) sites, a research aircraft, and a research vessel characterized 3-dimensional atmospheric boundary layer structures over the Houston-Galveston Bay area, providing a unique opportunity for the evaluation of the physical parameterizations. The model simulations were performed over the Houston metropolitan area for a summertime period (12–17 August) using a bulk urban parameterization in the Noah land surface model (original LSM), a modified LSM, and a single-layer urban canopy model (UCM). The UCM simulation compared quite well with the observations over the Houston urban areas, reducing the systematic model biases in the original LSM simulation by 1–2 °C in near-surface air temperature and by 200–400 m in UBL height, on average. A more realistic turbulent (sensible and latent heat) energy partitioning contributed to the improvements in the UCM simulation. The original LSM significantly overestimated the sensible heat flux (~200 W m−2) over the urban areas, resulting in warmer and higher UBL. The modified LSM slightly reduced warm and high biases in near-surface air temperature (0.5–1 °C) and UBL height (~100 m) as a result of the effects of urban vegetation. The relatively strong thermal contrast between the Houston area and the water bodies (Galveston Bay and the Gulf of Mexico) in the LSM simulations enhanced the sea/bay breezes, but the model performance in predicting local wind fields was similar among the simulations in terms of statistical evaluations. These results suggest that a proper surface representation (e.g. urban vegetation, surface morphology) and explicit parameterizations of urban physical processes are required for accurate urban atmospheric numerical modeling.

scholarly journals Evaluation of urban surface parameterizations in the WRF model using measurements during the Texas Air Quality Study 2006 field campaign

2010 ◽  
Vol 10 (10) ◽  
pp. 25033-25080 ◽  
Author(s):  
S.-H. Lee ◽  
S.-W. Kim ◽  
W. M. Angevine ◽  
L. Bianco ◽  
S. A. McKeen ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Air Quality ◽  
Surface Temperature ◽  
Latent Heat ◽  
Urban Boundary Layer ◽  
Urban Surface ◽  
Urban Vegetation ◽  
Field Campaign ◽  
Quality Study ◽  
Surface Parameterizations

Abstract. The impact of urban surface parameterizations in the WRF (Weather Research and Forecasting) model on the simulation of local meteorological fields is investigated. The Noah land surface model (LSM), a modified LSM, and a single-layer urban canopy model (UCM) have been compared, focusing on urban patches. The model simulations were performed for 6 days from 12 August to 17 August during the Texas Air Quality Study 2006 field campaign. Analysis was focused on the Houston-Galveston metropolitan area. The model simulated temperature, wind, and atmospheric boundary layer (ABL) height were compared with observations from surface meteorological stations (Continuous Ambient Monitoring Stations, CAMS), wind profilers, the NOAA Twin Otter aircraft, and the NOAA Research Vessel Ronald H. Brown. The UCM simulation showed better results in the comparison of ABL height and surface temperature than the LSM simulations, whereas the original LSM overestimated both the surface temperature and ABL height significantly in urban areas. The modified LSM, which activates hydrological processes associated with urban vegetation mainly through transpiration, slightly reduced warm and high biases in surface temperature and ABL height. A comparison of surface energy balance fluxes in an urban area indicated the UCM reproduces a realistic partitioning of sensible heat and latent heat fluxes, consequently improving the simulation of urban boundary layer. However, the LSMs have a higher Bowen ratio than the observation due to significant suppression of latent heat flux. The comparison results suggest that the subgrid heterogeneity by urban vegetation and urban morphological characteristics should be taken into account along with the associated physical parameterizations for accurate simulation of urban boundary layer if the region of interest has a large fraction of vegetation within the urban patch. Model showed significant discrepancies in the specific meteorological conditions when nocturnal low-level jets exist and a thermal internal boundary layer over water forms.

scholarly journals Numerical simulations of the impact of the 20 March 2015 eclipse on UK weather

2016 ◽  
Vol 374 (2077) ◽  
pp. 20150218 ◽  
Author(s):  
P. A. Clark
Keyword(s):  
Boundary Layer ◽  
Air Temperature ◽  
Urban Areas ◽  
Weather Prediction ◽  
Sensible Heat Flux ◽  
Thermal Inertia ◽  
Surface Air Temperature ◽  
Atmospheric Effects ◽  
Near Surface ◽  
The Impact

Short lead-time forecasts using the operational United Kingdom variable-resolution (UKV) configuration of the Met Office’s numerical weather prediction model, with horizontal grid-length 1.5 km over the UK, with and without a representation of the 20 March 2015 eclipse, have been used to simulate the impact of the eclipse on UK weather. The major impact was surface-driven through changes to surface heat and moisture fluxes that changed the boundary-layer development. In cloud-free areas, the nocturnal stable boundary layer persisted or quickly re-established during the eclipse. Surface temperatures were reduced by 7–8°C, near-surface air temperature by 1–3°C, and near-surface winds were backed, typically by 20°. Impacts on wind speed were small and variable, and would have been very difficult to detect. Smaller impacts occurred beneath cloud. However, the impact was enhanced because most of the incoming radiation that reached the surface was driving surface sensible heat flux rather than moisture flux, and the near-surface air temperature impact (0.5–1° C ) agrees reasonably well with observations. The modelled impact of the eclipse was substantially reduced in urban areas due to their large thermal inertia. Experience from other assessments of the model suggests that this lack of response may be exaggerated. Surface impacts propagated upwards and downstream with time, resulting in a complex pattern of response, though generally near-surface temperature differences persisted for many hours after the eclipse. The impact on atmospheric pressure fields was insufficient to account for any significant perturbations to the wind field when compared with the direct impacts of surface stress and boundary-layer mixing. This article is part of the themed issue ‘Atmospheric effects of solar eclipses stimulated by the 2015 UK eclipse’.

scholarly journals Effectiveness of Different Urban Heat Island Mitigation Methods and Their Regional Impacts

2017 ◽  
Vol 18 (11) ◽  
pp. 2991-3012 ◽  
Author(s):  
Ning Zhang ◽  
Yan Chen ◽  
Ling Luo ◽  
Yongwei Wang
Keyword(s):  
Boundary Layer ◽  
Urban Heat Island ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Green Roofs ◽  
Heat Island ◽  
Near Surface ◽  
Regional Impacts ◽  
Urban Heat ◽  
Cool Roofs

Abstract Cool roofs and green roofs are two popular methods to mitigate the urban heat island and improve urban climates. The effectiveness of different urban heat island mitigation strategies in the summer of 2013 in the Yangtze River delta, China, is investigated using the Weather Research and Forecasting (WRF) Model coupled with a physically based single-layer urban canopy model. The modifications to the roof surface changed the urban surface radiation balance and then modified the local surface energy budget. Both cool roofs and green roofs led to a lower surface skin temperature and near-surface air temperature. Increasing the roof albedo to 0.5 caused a similar effectiveness as covering 25% of urban roofs with vegetation; increasing the roof albedo to 0.7 caused a similar near-surface air temperature decrease as 50% green roof coverage. The near-surface relative humidity increased in both cool roof and green roof experiments because of the combination of the impacts of increases in specific humidity and decreases in air temperature. The regional impacts of cool roofs and green roofs were evaluated using a regional effect index. A regional impact was found for near-surface air temperature and specific/relative humidity when the percentage of roofs covered with high-albedo materials or green roofs reached a higher fraction (greater than 50%). The changes in the vertical profiles of temperature cause a more stable atmospheric boundary layer over the urban area; at the same time, the crossover phenomena occurred above the boundary layer due to the decrease in vertical wind speed.

scholarly journals Evaluation and Comparison of Noah and Pleim–Xiu Land Surface Models in MM5 Using GÖTE2001 Data: Spatial and Temporal Variations in Near-Surface Air Temperature

2007 ◽  
Vol 46 (10) ◽  
pp. 1587-1605 ◽  
Author(s):  
J-F. Miao ◽  
D. Chen ◽  
K. Borne
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Land Surface ◽  
Model Performance ◽  
Surface Air Temperature ◽  
Near Surface ◽  
Surface Models ◽  
Urban Heat ◽  
Soil Moisture Initialization ◽  
Evident Difference

Abstract In this study, the performance of two advanced land surface models (LSMs; Noah LSM and Pleim–Xiu LSM) coupled with the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), version 3.7.2, in simulating the near-surface air temperature in the greater Göteborg area in Sweden is evaluated and compared using the GÖTE2001 field campaign data. Further, the effects of different planetary boundary layer schemes [Eta and Medium-Range Forecast (MRF) PBLs] for Noah LSM and soil moisture initialization approaches for Pleim–Xiu LSM are investigated. The investigation focuses on the evaluation and comparison of diurnal cycle intensity and maximum and minimum temperatures, as well as the urban heat island during the daytime and nighttime under the clear-sky and cloudy/rainy weather conditions for different experimental schemes. The results indicate that 1) there is an evident difference between Noah LSM and Pleim–Xiu LSM in simulating the near-surface air temperature, especially in the modeled urban heat island; 2) there is no evident difference in the model performance between the Eta PBL and MRF PBL coupled with the Noah LSM; and 3) soil moisture initialization is of crucial importance for model performance in the Pleim–Xiu LSM. In addition, owing to the recent release of MM5, version 3.7.3, some experiments done with version 3.7.2 were repeated to reveal the effects of the modifications in the Noah LSM and Pleim–Xiu LSM. The modification to longwave radiation parameterizations in Noah LSM significantly improves model performance while the adjustment of emissivity, one of the vegetation properties, affects Pleim–Xiu LSM performance to a larger extent. The study suggests that improvements both in Noah LSM physics and in Pleim–Xiu LSM initialization of soil moisture and parameterization of vegetation properties are important.

scholarly journals Nature-based cooling potential: a multi-type green infrastructure evaluation in Toronto, Ontario, Canada

2021 ◽  
Author(s):  
Vidya Anderson ◽  
William A. Gough
Keyword(s):  
Urban Agriculture ◽  
Air Temperature ◽  
Green Infrastructure ◽  
Urban Climate ◽  
Surface Air Temperature ◽  
Green Roofs ◽  
Near Surface ◽  
Green Walls ◽  
The Impact ◽  
Agriculture Systems

AbstractThe application of green infrastructure presents an opportunity to mitigate rising temperatures using a multi-faceted ecosystems-based approach. A controlled field study in Toronto, Ontario, Canada, evaluates the impact of nature-based solutions on near surface air temperature regulation focusing on different applications of green infrastructure. A field campaign was undertaken over the course of two summers to measure the impact of green roofs, green walls, urban vegetation and forestry systems, and urban agriculture systems on near surface air temperature. This study demonstrates that multiple types of green infrastructure applications are beneficial in regulating near surface air temperature and are not limited to specific treatments. Widespread usage of green infrastructure could be a viable strategy to cool cities and improve urban climate.

Evaluating temperature extremes in CMIP6 simulations using statistically proper evaluation methods

2021 ◽  
Author(s):  
Thordis Thorarinsdottir ◽  
Jana Sillmann ◽  
Marion Haugen ◽  
Nadine Gissibl ◽  
Marit Sandstad
Keyword(s):  
Air Temperature ◽  
Model Evaluation ◽  
Climate Models ◽  
Climate Model ◽  
Mean Squared Error ◽  
Surface Air Temperature ◽  
Cmip5 Models ◽  
Model Output ◽  
Intergovernmental Panel ◽  
Near Surface

<p>Reliable projections of extremes in near-surface air temperature (SAT) by climate models become more and more important as global warming is leading to significant increases in the hottest days and decreases in coldest nights around the world with considerable impacts on various sectors, such as agriculture, health and tourism.</p><p>Climate model evaluation has traditionally been performed by comparing summary statistics that are derived from simulated model output and corresponding observed quantities using, for instance, the root mean squared error (RMSE) or mean bias as also used in the model evaluation chapter of the fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). Both RMSE and mean bias compare averages over time and/or space, ignoring the variability, or the uncertainty, in the underlying values. Particularly when interested in the evaluation of climate extremes, climate models should be evaluated by comparing the probability distribution of model output to the corresponding distribution of observed data.</p><p>To address this shortcoming, we use the integrated quadratic distance (IQD) to compare distributions of simulated indices to the corresponding distributions from a data product. The IQD is the proper divergence associated with the proper continuous ranked probability score (CRPS) as it fulfills essential decision-theoretic properties for ranking competing models and testing equality in performance, while also assessing the full distribution.</p><p>The IQD is applied to evaluate CMIP5 and CMIP6 simulations of monthly maximum (TXx) and minimum near-surface air temperature (TNn) over the data-dense regions Europe and North America against both observational and reanalysis datasets. There is not a notable difference between the model generations CMIP5 and CMIP6 when the model simulations are compared against the observational dataset HadEX2. However, the CMIP6 models show a better agreement with the reanalysis ERA5 than CMIP5 models, with a few exceptions. Overall, the climate models show higher skill when compared against ERA5 than when compared against HadEX2. While the model rankings vary with region, season and index, the model evaluation is robust against changes in the grid resolution considered in the analysis.</p>

scholarly journals Biogenic isoprene emissions driven by regional weather predictions using different initialization methods: case studies during the SEAC<sup>4</sup>RS and DISCOVER-AQ airborne campaigns

2017 ◽  
Vol 10 (8) ◽  
pp. 3085-3104 ◽  
Author(s):  
Min Huang ◽  
Gregory R. Carmichael ◽  
James H. Crawford ◽  
Armin Wisthaler ◽  
Xiwu Zhan ◽  
...  
Keyword(s):  
Case Studies ◽  
Air Temperature ◽  
Initial Conditions ◽  
Wrf Model ◽  
Surface Air Temperature ◽  
Heat Fluxes ◽  
Aircraft Observation ◽  
Near Surface ◽  
Boundary Layer Height ◽  
Small Scales

Abstract. Land and atmospheric initial conditions of the Weather Research and Forecasting (WRF) model are often interpolated from a different model output. We perform case studies during NASA's SEAC4RS and DISCOVER-AQ Houston airborne campaigns, demonstrating that using land initial conditions directly downscaled from a coarser resolution dataset led to significant positive biases in the coupled NASA-Unified WRF (NUWRF, version 7) surface and near-surface air temperature and planetary boundary layer height (PBLH) around the Missouri Ozarks and Houston, Texas, as well as poorly partitioned latent and sensible heat fluxes. Replacing land initial conditions with the output from a long-term offline Land Information System (LIS) simulation can effectively reduce the positive biases in NUWRF surface air temperature by ∼ 2 °C. We also show that the LIS land initialization can modify surface air temperature errors almost 10 times as effectively as applying a different atmospheric initialization method. The LIS-NUWRF-based isoprene emission calculations by the Model of Emissions of Gases and Aerosols from Nature (MEGAN, version 2.1) are at least 20 % lower than those computed using the coarser resolution data-initialized NUWRF run, and are closer to aircraft-observation-derived emissions. Higher resolution MEGAN calculations are prone to amplified discrepancies with aircraft-observation-derived emissions on small scales. This is possibly a result of some limitations of MEGAN's parameterization and uncertainty in its inputs on small scales, as well as the representation error and the neglect of horizontal transport in deriving emissions from aircraft data. This study emphasizes the importance of proper land initialization to the coupled atmospheric weather modeling and the follow-on emission modeling. We anticipate it to also be critical to accurately representing other processes included in air quality modeling and chemical data assimilation. Having more confidence in the weather inputs is also beneficial for determining and quantifying the other sources of uncertainties (e.g., parameterization, other input data) of the models that they drive.

scholarly journals PARAMETERS OF INTEREST FOR THE DESIGN OF GREEN INFRASTRUCTURE

2019 ◽  
pp. 92-101
Author(s):  
Marija Šperac ◽  
Dino Obradović
Keyword(s):  
Air Quality ◽  
Urban Environment ◽  
Air Temperature ◽  
Green Infrastructure ◽  
Land Surface ◽  
Urban Areas ◽  
Hydrological Cycle ◽  
Urban Environments ◽  
Land Surfaces ◽  
Selection Of

The urbanization process significantly reduced the permeability of land surfaces, which affected the changes of runoff characteristics and the relations in the hydrological cycle. In urban environments, the relationships within the hydrological cycle have changed in quantity, in particular: precipitation, air temperature, evaporation, and infiltration. By applying the green infrastructure (GI) to urban environments is beneficial for the water resources and the social community. GI has an effect on the improvement of ecological, economic, and social conditions. Using GI into urban areas increases the permeability of land surfaces, whereby decreasing surface runoff, and thus the frequency of urban floods. It also has a significant influence on the regulation of air quality, water purification, climate change impact, and the changes in the appearance of the urban environment. When planning and designing the GI, it is necessary to identify the type of GI and determine the size and location of the selected GI. Since each urban environment has its own characteristics, it is necessary to analyze them before deciding on the GI. The paper analyzed meteorological parameters (precipitation, air temperature, insolation, air humidity) affecting the selection of GI types, using the specific example of an urban environment – the City of Osijek, Croatia. Significant parameters when designing GI are operation and maintenance These parameters directly affect the efficiency of GI. The proper selection of GI and its location results in maximum gains: the reduction of land surface drainage - drainage of the sewage system, purification and retention of precipitation at the place of production, the improvement of air quality, and the improvement of living conditions in urban environments

scholarly journals Near–surface air temperature and snow skin temperature comparison from CREST-SAFE station data with MODIS land surface temperature data

2015 ◽  
Vol 12 (8) ◽  
pp. 7665-7687 ◽  
Author(s):  
C. L. Pérez Díaz ◽  
T. Lakhankar ◽  
P. Romanov ◽  
J. Muñoz ◽  
R. Khanbilvardi ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Skin Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Critical Role ◽  
Surface Air Temperature ◽  
Balance Model ◽  
Near Surface

Abstract. Land Surface Temperature (LST) is a key variable (commonly studied to understand the hydrological cycle) that helps drive the energy balance and water exchange between the Earth's surface and its atmosphere. One observable constituent of much importance in the land surface water balance model is snow. Snow cover plays a critical role in the regional to global scale hydrological cycle because rain-on-snow with warm air temperatures accelerates rapid snow-melt, which is responsible for the majority of the spring floods. Accurate information on near-surface air temperature (T-air) and snow skin temperature (T-skin) helps us comprehend the energy and water balances in the Earth's hydrological cycle. T-skin is critical in estimating latent and sensible heat fluxes over snow covered areas because incoming and outgoing radiation fluxes from the snow mass and the air temperature above make it different from the average snowpack temperature. This study investigates the correlation between MODerate resolution Imaging Spectroradiometer (MODIS) LST data and observed T-air and T-skin data from NOAA-CREST-Snow Analysis and Field Experiment (CREST-SAFE) for the winters of 2013 and 2014. LST satellite validation is imperative because high-latitude regions are significantly affected by climate warming and there is a need to aid existing meteorological station networks with the spatially continuous measurements provided by satellites. Results indicate that near-surface air temperature correlates better than snow skin temperature with MODIS LST data. Additional findings show that there is a negative trend demonstrating that the air minus snow skin temperature difference is inversely proportional to cloud cover. To a lesser extent, it will be examined whether the surface properties at the site are representative for the LST properties within the instrument field of view.

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