Weather Research Forecast (WRF) modification of land surface albedo simulations for urban Near Surface Temperature

Author(s):  
Siti Aekbal Salleh ◽  
Zulkiflee Abd Latif ◽  
Andy Chan ◽  
Kenobi Isima Morris ◽  
Maggie Chel Gee Ooi ◽  
...  
2011 ◽  
Vol 7 (1) ◽  
pp. 17-25 ◽  
Author(s):  
Y. Hu ◽  
J. Yang ◽  
F. Ding ◽  
W. R. Peltier

Abstract. One of the critical issues of the Snowball Earth hypothesis is the CO2 threshold for triggering the deglaciation. Using Community Atmospheric Model version 3.0 (CAM3), we study the problem for the CO2 threshold. Our simulations show large differences from previous results (e.g. Pierrehumbert, 2004, 2005; Le Hir et al., 2007). At 0.2 bars of CO2, the January maximum near-surface temperature is about 268 K, about 13 K higher than that in Pierrehumbert (2004, 2005), but lower than the value of 270 K for 0.1 bar of CO2 in Le Hir et al. (2007). It is found that the difference of simulation results is mainly due to model sensitivity of greenhouse effect and longwave cloud forcing to increasing CO2. At 0.2 bars of CO2, CAM3 yields 117 Wm−2 of clear-sky greenhouse effect and 32 Wm−2 of longwave cloud forcing, versus only about 77 Wm−2 and 10.5 Wm−2 in Pierrehumbert (2004, 2005), respectively. CAM3 has comparable clear-sky greenhouse effect to that in Le Hir et al. (2007), but lower longwave cloud forcing. CAM3 also produces much stronger Hadley cells than that in Pierrehumbert (2005). Effects of pressure broadening and collision-induced absorption are also studied using a radiative-convective model and CAM3. Both effects substantially increase surface temperature and thus lower the CO2 threshold. The radiative-convective model yields a CO2 threshold of about 0.21 bars with surface albedo of 0.663. Without considering the effects of pressure broadening and collision-induced absorption, CAM3 yields an approximate CO2 threshold of about 1.0 bar for surface albedo of about 0.6. However, the threshold is lowered to 0.38 bars as both effects are considered.


2015 ◽  
Vol 12 (8) ◽  
pp. 7665-7687 ◽  
Author(s):  
C. L. Pérez Díaz ◽  
T. Lakhankar ◽  
P. Romanov ◽  
J. Muñoz ◽  
R. Khanbilvardi ◽  
...  

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.


2019 ◽  
Vol 11 (20) ◽  
pp. 2369 ◽  
Author(s):  
Ahmed M. El Kenawy ◽  
Mohamed E. Hereher ◽  
Sayed M. Robaa

Space-based data have provided important advances in understanding climate systems and processes in arid and semi-arid regions, which are hot-spot regions in terms of climate change and variability. This study assessed the performance of land surface temperatures (LSTs), retrieved from the Moderate-Resolution Imaging Spectroradiometer (MODIS) Aqua platform, over Egypt. Eight-day composites of daytime and nighttime LST data were aggregated and validated against near-surface seasonal and annual observational maximum and minimum air temperatures using data from 34 meteorological stations spanning the period from July 2002 to June 2015. A variety of accuracy metrics were employed to evaluate the performance of LST, including the bias, normalized root-mean-square error (nRMSE), Yule–Kendall (YK) skewness measure, and Spearman’s rho coefficient. The ability of LST to reproduce the seasonal cycle, anomalies, temporal variability, and the distribution of warm and cold tails of observational temperatures was also evaluated. Overall, the results indicate better performance of the nighttime LSTs compared to the daytime LSTs. Specifically, while nighttime LST tended to underestimate the minimum air temperature during winter, spring, and autumn on the order of −1.3, −1.2, and −1.4 °C, respectively, daytime LST markedly overestimated the maximum air temperature in all seasons, with values mostly above 5 °C. Importantly, the results indicate that the performance of LST over Egypt varies considerably as a function of season, lithology, and land use. LST performs better during transitional seasons (i.e., spring and autumn) compared to solstices (i.e., winter and summer). The varying interactions and feedbacks between the land surface and the atmosphere, especially the differences between sensible and latent heat fluxes, contribute largely to these seasonal variations. Spatially, LST performs better in areas with sandstone formations and quaternary sediments and, conversely, shows lower accuracy in regions with limestone, igneous, and metamorphic rocks. This behavior can be expected in hybrid arid and semi-arid regions like Egypt, where bare rocks contribute to the majority of the Egyptian territory, with a lack of vegetation cover. The low surface albedo of igneous and limestone rocks may explain the remarkable overestimation of daytime temperature in these regions, compared to the bright formations of higher surface albedo (i.e., sandy deserts and quaternary rocks). Overall, recalling the limited coverage of meteorological stations in Egypt, this study demonstrates that LST obtained from the MODIS product can be trustworthily employed as a surrogate for or a supplementary source to near-surface measurements, particularly for minimum air temperature. On the other hand, some bias correction techniques should be applied to daytime LSTs. In general, the fine space-based climatic information provided by MODIS LST can be used for a detailed spatial assessment of climate variability in Egypt, with important applications in several disciplines such as water resource management, hydrological modeling, agricultural management and planning, urban climate, biodiversity, and energy consumption, amongst others. Also, this study can contribute to a better understanding of the applications of remote sensing technology in assessing climatic feedbacks and interactions in arid and semi-arid regions, opening new avenues for developing innovative algorithms and applications specifically addressing issues related to these regions.


2020 ◽  
Vol 242 ◽  
pp. 111746 ◽  
Author(s):  
Mohammad Karimi Firozjaei ◽  
Solmaz Fathololoumi ◽  
Seyed Kazem Alavipanah ◽  
Majid Kiavarz ◽  
Ali Reza Vaezi ◽  
...  

2017 ◽  
Vol 145 (12) ◽  
pp. 4727-4745 ◽  
Author(s):  
Elena Tomasi ◽  
Lorenzo Giovannini ◽  
Dino Zardi ◽  
Massimiliano de Franceschi

The paper presents the results of high-resolution simulations performed with the WRF Model, coupled with two different land surface schemes, Noah and Noah_MP, with the aim of accurately reproducing winter season meteorological conditions in a typical Alpine valley. Accordingly, model results are compared against data collected during an intensive field campaign performed in the Adige Valley, in the eastern Italian Alps. In particular, the ability of the model in reproducing the time evolution of 2-m temperature and of incoming and outgoing shortwave and longwave radiation is examined. The validation of model results highlights that, in this context, WRF reproduces rather poorly near-surface temperature over snow-covered terrain, with an evident underestimation, during both daytime and nighttime. Furthermore it fails to capture specific atmospheric processes, such as the temporal evolution of the ground-based thermal inversion. The main cause of these errors lies in the miscalculation of the mean gridcell albedo, resulting in an inaccurate estimate of the reflected solar radiation calculated by both Noah and Noah_MP. Therefore, modifications to the initialization, to the land-use classification, and to both land surface models are performed to improve model results, by intervening in the calculation of the albedo, of the snow cover, and of the surface temperature. Qualitative and quantitative analyses show that, after these changes, a significant improvement in the comparability between model results and observations is achieved. In particular, outgoing shortwave radiation is lowered, 2-m temperature maxima increased accordingly, and ground-based thermal inversions are better captured.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Chunlei Meng ◽  
Huoqing Li

AbstractFengyun-4A is the new generation of Chinese geostationary meteorological satellites. Land surface albedo, land surface emissivity and land surface temperature are key states for land surface modelling. In this paper, the land surface albedo, land surface emissivity and land surface temperature data from Fengyun-4A were assimilated into the Integrated Urban land Model. The Fengyun-4A data are one of the data sources for the land data assimilation system which devoted to produce the high spatial and temporal resolution, multiple parameters near real-time land data sets. The Moderate-Resolution Imaging Spectroradiometer (MODIS) LSA and LSE data, the Institute of Atmospheric Physics, China Academy of Sciences (IAP) 325 m tower observation data and the observed 5 cm and 10 cm soil temperature data in more than 100 sites are used for validation. The results indicate the MODIS land surface albedo is much smaller than the Fengyun-4A and is superior to the Fengyun-4A for the Institute of Atmospheric Physics, China Academy of Sciences 325 m tower site. The Moderate-Resolution Imaging Spectroradiometer land surface emissivity is smaller than the Fengyun-4A in barren land surface and the differences is relatively small for other land use and land cover categories. In most regions of the research area, the Fengyun-4A land surface albedo and land surface emissivity are larger than those of the simulations. After the land surface albedo assimilation, in most regions the simulated net radiation was decreased. After the land surface emissivity assimilation, in most regions the simulated net radiation was increased. After the land surface temperature assimilation, the biases of the land surface temperature were decreased apparently; the biases of the daily average 5 cm and 10 cm soil temperature were decreased.


2006 ◽  
Vol 19 (12) ◽  
pp. 2995-3003 ◽  
Author(s):  
Yuichiro Oku ◽  
Hirohiko Ishikawa ◽  
Shigenori Haginoya ◽  
Yaoming Ma

Abstract The diurnal, seasonal, and interannual variations in land surface temperature (LST) on the Tibetan Plateau from 1996 to 2002 are analyzed using the hourly LST dataset obtained by Japanese Geostationary Meteorological Satellite 5 (GMS-5) observations. Comparing LST retrieved from GMS-5 with independent precipitation amount data demonstrates the consistent and complementary relationship between them. The results indicate an increase in the LST over this period. The daily minimum has risen faster than the daily maximum, resulting in a narrowing of the diurnal range of LST. This is in agreement with the observed trends in both global and plateau near-surface air temperature. Since the near-surface air temperature is mainly controlled by LST, this result ensures a warming trend in near-surface air temperature.


2020 ◽  
Author(s):  
Zheng Guo ◽  
Miaomiao Cheng

<p>Diurnal temperature range (includes land surface temperature diurnal range and near surface air temperature diurnal range) is an important meteorological parameter, which is a very important factor in the field of the urban thermal environmental. Nowadays, the research of urban thermal environment mainly focused on surface heat island and canopy heat island.</p><p>Based on analysis of the current status of city thermal environment. Firstly, a method was proposed to obtain near surface air temperature diurnal range in this study, difference of land surface temperature between day and night were introduced into the improved temperature vegetation index feature space based on remote sensing data. Secondly, compared with the district administrative division, we analyzed the spatial and temporal distribution characteristics of the diurnal range of land surface temperature and near surface air temperature.</p><p>The conclusions of this study are as follows:</p><p>1 During 2003-2012s, the land surface temperature and near surface air temperature diurnal range of Beijing were fluctuating upward. The rising trend of the near surface air temperature diurnal range was more significant than land surface temperature diurnal range. In addition, the rise and decline of land surface temperature and near surface air temperature diurnal range in different districts were different. In the six city districts, the land surface temperature and near surface air temperature diurnal range in the six areas of the city were mainly downward. The decline trend of near surface air temperature diurnal range was more significant than land surface temperature diurnal range.</p><p>2 During 2003-2012s, the land surface temperature and near surface air temperature diurnal range of Beijing with similar characteristics in spatial distribution, with higher distribution land surface temperature and near surface air temperature diurnal range in urban area and with lower distribution of land surface temperature and near surface air temperature diurnal range in the Northwest Mountainous area and the area of Miyun reservoir.</p>


2012 ◽  
Vol 13 (2) ◽  
pp. 521-538 ◽  
Author(s):  
Emanuel Dutra ◽  
Pedro Viterbo ◽  
Pedro M. A. Miranda ◽  
Gianpaolo Balsamo

Abstract Three different complexity snow schemes implemented in the ECMWF land surface scheme Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) are evaluated within the EC-EARTH climate model. The snow schemes are (i) the original HTESSEL single-bulk-layer snow scheme, (ii) a new snow scheme in operations at ECMWF since September 2009, and (iii) a multilayer version of the previous. In offline site simulations, the multilayer scheme outperforms the single-layer schemes in deep snowpack conditions through its ability to simulate sporadic melting events thanks to the lower thermal inertial of the uppermost layer. Coupled atmosphere–land/snow simulations performed by the EC-EARTH climate model are validated against remote sensed snow cover and surface albedo. The original snow scheme has a systematic early melting linked to an underestimation of surface albedo during spring that was partially reduced with the new snow schemes. A key process to improve the realism of the near-surface atmospheric temperature and at the same time the soil freezing is the thermal insulation of the snowpack (tightly coupled with the accuracy of snow mass and density simulations). The multilayer snow scheme outperforms the single-layer schemes in open deep snowpack (such as prairies or tundra in northern latitudes) and is instead comparable in shallow snowpack conditions. However, the representation of orography in current climate models implies limitations for accurately simulating the snowpack, particularly over complex terrain regions such as the Rockies and the Himalayas.


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