scholarly journals Global Contributions of Incoming Radiation and Land Surface Conditions to Maximum Near-Surface Air Temperature Variability and Trend

2018 ◽  
Vol 45 (10) ◽  
pp. 5034-5044 ◽  
Author(s):  
Clemens Schwingshackl ◽  
Martin Hirschi ◽  
Sonia I. Seneviratne
Keyword(s):  
Air Temperature ◽  
Land Surface ◽  
Surface Air Temperature ◽  
Temperature Variability ◽  
Near Surface ◽  
Surface Conditions ◽  
Incoming Radiation

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 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.

Recent Trends in Land Surface Temperature on the Tibetan Plateau

2006 ◽  
Vol 19 (12) ◽  
pp. 2995-3003 ◽  
Author(s):  
Yuichiro Oku ◽  
Hirohiko Ishikawa ◽  
Shigenori Haginoya ◽  
Yaoming Ma
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Precipitation Amount ◽  
Surface Air Temperature ◽  
The Tibetan Plateau ◽  
Near Surface ◽  
Diurnal Range

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.

Study on Urban Thermal Environment based on Diurnal Temperature Range

2020 ◽  
Author(s):  
Zheng Guo ◽  
Miaomiao Cheng
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Thermal Environment ◽  
Surface Air Temperature ◽  
Heat Island ◽  
Near Surface ◽  
Diurnal Range ◽  
Urban Thermal Environment

<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>

scholarly journals Summer- and Wintertime Variations of the Surface and Near-Surface Urban Heat Island in a Semiarid Environment

2019 ◽  
Vol 34 (6) ◽  
pp. 1849-1865
Author(s):  
Francisco Salamanca Palou ◽  
Alex Mahalov
Keyword(s):  
Air Temperature ◽  
Land Surface ◽  
Wrf Model ◽  
Surface Air Temperature ◽  
Near Surface ◽  
Urban Rural ◽  
Urban Cool Island ◽  
Surface Skin Temperature ◽  
Urban Heat ◽  
Surface Urban Heat Island

Abstract This paper examines summer- and wintertime variations of the surface and near-surface urban heat island (UHI) for the Phoenix metropolitan area using the Moderate Resolution Imaging Spectroradiometer (MODIS), near-surface meteorological observations, and the Weather Research and Forecasting (WRF) Model during a 31-day summer- and a 31-day wintertime period. The surface UHI (defined based on the urban–rural land surface temperature difference) is found to be higher at night and during the warm season. On the other hand, the morning surface UHI is low and frequently exhibits an urban cool island that increases during the summertime period. Similarly, the near-surface UHI (defined based on the urban–rural 2-m air temperature difference) is higher at night and during summertime. On the other hand, the daytime near-surface UHI is low but rarely exhibits an urban cool island. To evaluate the WRF Model’s ability to reproduce the diurnal cycle of near-surface meteorology and surface skin temperature, two WRF Model experiments (one using the Bougeault and Lacarrere turbulent scheme and one with the Mellor–Yamada–Janjić turbulent parameterization) at high spatial resolution (1-km horizontal grid spacing) are conducted for each 31-day period. Modeled results show that the WRF Model (coupled to the Noah-MP land surface model) tends to underestimate to some extent surface skin temperature during daytime and overestimate nighttime values during the wintertime period. In the same way, the WRF Model tends to accurately reproduce the diurnal cycle of near-surface air temperature, including maximum and minimum temperatures, and wind speed during summertime, but notably overestimates nighttime near-surface air temperature during wintertime. This nighttime overestimation is especially remarkable with the Bougeault and Lacarrere turbulent scheme for both urban and rural areas.

scholarly journals Different response of surface temperature and air temperature to deforestation in climate models

2018 ◽  
Author(s):  
Johannes Winckler ◽  
Christian H. Reick ◽  
Sebastiaan Luyssaert ◽  
Alessandro Cescatti ◽  
Paul C. Stoy ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface ◽  
Model Comparison ◽  
Climate Models ◽  
Surface Air Temperature ◽  
Atmospheric Layer ◽  
Nonlocal Effects ◽  
Local Effects ◽  
Near Surface

Abstract. Deforestation affects temperatures at the land surface and higher up in the atmosphere. Satellite-based observations typically register deforestation-induced changes in surface temperature, in-situ observations register changes in near-surface air temperature, and climate models simulate changes in both temperatures and the temperature of the lowest atmospheric layer. Yet a focused analysis of how these variables respond differently to deforestation is missing. Here, this is investigated by analyzing the biogeophysical temperature effects of large-scale deforestation in the climate model MPI-ESM, separately for local effects (which are only apparent at the location of deforestation) and nonlocal effects (which are also apparent elsewhere). While the nonlocal effects affect the temperature of the surface and lowest atmospheric layer equally, the local effects mainly affect the temperature of the surface. In agreement with observation-based studies, the local effects on surface and near-surface air temperature respond differently in the MPI-ESM, both concerning the magnitude of local temperature changes and the latitude at which the local deforestation effects turn from a cooling to a warming (at 45–55° N for surface temperature and around 35° N for near-surface air temperature). An inter-model comparison shows that in the northern mid latitudes, both for summer and winter, near-surface air temperature is affected by the 5local effects only about half as much compared to surface temperature. Thus, studies about the biogeophysical effects of deforestation must carefully choose which temperature they consider.

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