scholarly journals Creating New Near-Surface Air Temperature Datasets to Understand Elevation-Dependent Warming in the Tibetan Plateau

2020 ◽  
Vol 12 (11) ◽  
pp. 1722
Author(s):  
Mingxi Zhang ◽  
Bin Wang ◽  
James Cleverly ◽  
De Li Liu ◽  
Puyu Feng ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Air Temperature ◽  
Land Surface ◽  
Vegetation Indices ◽  
Surface Air Temperature ◽  
The Tibetan Plateau ◽  
Global Studies ◽  
Near Surface ◽  
Automated Mapping ◽  
Land Surface Temperatures

The Tibetan Plateau has been undergoing accelerated warming over recent decades, and is considered an indicator for broader global warming phenomena. However, our understanding of warming rates with elevation in complex mountain regions is incomplete. The most serious concern is the lack of high-quality near-surface air temperature (Tair) datasets in these areas. To address this knowledge gap, we developed an automated mapping framework for the estimation of seamless daily minimum and maximum Land Surface Temperatures (LSTs) for the Tibetan Plateau from the existing MODIS LST products for a long period of time (i.e., 2002–present). Specific machine learning methods were developed and linked with target-oriented validation and then applied to convert LST to Tair. Spatial variables in retrieving Tair, such as solar radiation and vegetation indices, were used in estimation of Tair, whereas MODIS LST products were mainly focused on temporal variation in surface air temperature. We validated our process using independent Tair products, revealing more reliable estimates on Tair; the R2 and RMSE at monthly scales generally fell in the range of 0.9–0.95 and 1–2 °C. Using these continuous and consistent Tair datasets, we found temperature increases in the elevation range between 2000–3000 m and 4000–5000 m, whereas the elevation interval at 6000–7000 m exhibits a cooling trend. The developed datasets, findings and methodology contribute to global studies on accelerated warming.

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.

scholarly journals Analysis On The Regional Features of Future Warming Using High-Resolution Downscaled Multi-Model Climate Scenarios In China

2021 ◽  
Author(s):  
Lei Zhang ◽  
Yinlong Xu ◽  
Chunchun Meng ◽  
Yuncheng Zhao ◽  
Changgui Wang
Keyword(s):  
Heat Stress ◽  
High Resolution ◽  
Tibetan Plateau ◽  
Air Temperature ◽  
South China ◽  
Surface Air Temperature ◽  
Northern China ◽  
The Tibetan Plateau ◽  
Near Surface ◽  
Future Warming

Abstract The frequency and magnitude of global warming events varies greatly across different regions and countries. The climatic diversity for China and future warming features are projected across twelve climatic zones based on the ensemble of the five well-performing high resolution downscaled climate models for each zone. There are warming patterns for the mean near surface air temperature (Tm), maximum near surface air temperature (Tmax), minimum near surface air temperature (Tmin) as well as heat stress and frost events. Under RCP4.5 and RCP8.5 scenarios, the three indices (i.e., Tm, Tmax and Tmin) countrywide are likely to increase at respective rates of 0.30-0.31 and 0.64-0.67 oC per decade. The extent of freezing-event extent (FE) are projected to decrease at a rate of -1912 and -4442 day·km2 per decade while the extent of heat-stress event (HE) increase at 1116 and 3557 day·km2 per decade. A higher increment in temperatures as well as a decreasing trend in the diurnal temperature range (DTR) and frost days and FE are present on the Tibetan Plateau and northern China including Xinjiang, Northeast China, the eastern part of northwest China, Inner Mongolia and North China. These trends are opposite to those projected for southern China including Huanghuai, Jianghuai, Jianghan, the south Yangzi River, South China and Southwestern China. The warming occur faster in the current colder zones (northern China and the Tibetan Plateau) while heat stress is more intense and severe in Jianghuai, Jianghan, the south Yangzi River, South China and Xinjiang. These potential changes indicate that adaption and mitigation strategies are necessary in response to future warming.

Accelerated Changes of Environmental Conditions on the Tibetan Plateau Caused by Climate Change

2011 ◽  
Vol 24 (24) ◽  
pp. 6540-6550 ◽  
Author(s):  
Lei Zhong ◽  
Zhongbo Su ◽  
Yaoming Ma ◽  
Mhd. Suhyb Salama ◽  
José A. Sobrino
Keyword(s):  
Heat Flux ◽  
Tibetan Plateau ◽  
Air Temperature ◽  
Land Surface ◽  
Asian Monsoon ◽  
Sensible Heat Flux ◽  
Surface Air Temperature ◽  
The Tibetan Plateau ◽  
Sensible Heat ◽  
Land Surface Parameters

Abstract Variations of land surface parameters over the Tibetan Plateau have great importance on local energy and water cycles, the Asian monsoon, and climate change studies. In this paper, the NOAA/NASA Pathfinder Advanced Very High Resolution Radiometer (AVHRR) Land (PAL) dataset is used to retrieve the land surface temperature (LST), the normalized difference vegetation index (NDVI), and albedo, from 1982 to 2000. Simultaneously, meteorological parameters and land surface heat fluxes are acquired from the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) dataset and the Global Land Data Assimilation System (GLDAS), respectively. Results show that from 1982 to 2000 both the LST and the surface air temperature increased on the Tibetan Plateau (TP). The rate of increase of the LST was 0.26±0.16 K decade−1 and that of the surface air temperature was 0.29 ± 0.16 K decade−1, which exceeded the increase in the Northern Hemisphere (0.054 K decade−1). The plateau-wide annual mean precipitation increased at 2.54 mm decade−1, which indicates that the TP is becoming wetter. The 10-m wind speed decreased at about 0.05±0.03 m s−1 decade−1 from 1982 to 2000, which manifests a steady decline of the Asian monsoon wind. Due to the diminishing ground–air temperature gradient and subdued surface wind speed, the sensible heat flux showed a decline of 3.37 ± 2.19 W m−2 decade−1. The seasonal cycle of land surface parameters could clearly be linked to the patterns of the Asian monsoon. The spatial patterns of sensible heat flux, latent heat flux, and their variance could also be recognized.

Estimating daily 1-km surface air temperature from satellite all-weather land surface temperature over the Tibetan Plateau

2020 ◽  
Author(s):  
Xin Wen ◽  
Ji Zhou ◽  
Xiaodong Zhang ◽  
Jin Ma
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Tibetan Plateau ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Climate Warming ◽  
Land Surface ◽  
Surface Air Temperature ◽  
Thermal Infrared ◽  
The Tibetan Plateau

<p>Over the past several decades, global climate change, particularly the rising temperature has caused public concerns. In the context of climate warming, many environmental and water problems such as decreasing runoff, shrinking glaciers and permafrost, vegetation degradation and desertification can be attributed to rapid climate change. Surface air temperature (SAT) plays a key role in land-atmospheric interactions and is an important parameter for climate change studies. Traditional SAT data are collected by ground meteorological observation. Nevertheless, such traditional measurements at ground stations cannot capture the spatial variations of SAT, especially over complicated areas such as the Tibetan Plateau, where meteorological stations are with large elevation variability and unreasonable spatial distribution. In contrast, satellite remote sensing provides an direct observation of land surface temperature (LST) and, thus, also provides an possible way to obtain SAT since LST and SAT are generally closely related to each other. The scientific communities have developed various methods to estimate SAT from LST through statistical or physical models. The widely used satellite LST, however, is derived from satellite thermal infrared remote sensing and thus, significantly affected by the clouds.</p><p>In this study, we report an examination of the estimation of daily 1-km SAT from the all-weather satellite LST over the Tibetan Plateau. The estimation of SAT is based on a noval method that dynamicall integrates the newly published 1-km all-weather LST data by merging satellite thermal infrared and microwave remote sensing observations based on the random forest. The matchups of the ground measured SAT at stations and the corresponding all-weather LST were separated into the training set and valiation set. In addition, independent SAT measured at experimental ground sites were used to evaluate the SAT method. Results indicate that reasonably integrating multiple LST terms provides daily average all-weather SAT with satisfactory accuracies over the Tibetan Plateau. The estimated SAT based on the proposed method has ignorable systematic error and low root-mean squared error when validated with ground measured SAT under all-weather conditions. Further comparison demonstrates that the SAT estimate agree well with other SAT estimated from satellite thermal infrared LST under cloud-free condition. In addition, the SAT method has the potential to be generalized and extended to various complicated areas. With this method, the daily 1-km SAT for the entire Tibetan Plateau from 2003 to 2018 were produced. This dataset is of great value to examine recent climate warming trend and the land-atmospheirc interactions in the entire Tibetan Plateau.</p>

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.

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