xiaoduo pan - Academia.edu (original) (raw)

Papers by xiaoduo pan

European Respiratory Journal, 2022

Allergen provocation test is an established model of allergic airway diseases, including asthma a... more Allergen provocation test is an established model of allergic airway diseases, including asthma and allergic rhinitis, allowing the study of allergen-induced changes in respiratory physiology and inflammatory mechanisms in sensitised individuals as well as their associations. In the upper airways, allergen challenge is focused on the clinical and pathophysiological sequelae of the early allergic response and applied both as a diagnostic tool and in research settings. In contrast, the bronchial allergen challenge has almost exclusively served as a research tool in specialised research settings with a focus on the late asthmatic response and the underlying type 2 inflammation. The allergen-induced late asthmatic response is also characterised by prolonged airway narrowing, increased non-specific airway hyperresponsiveness and features of airway remodelling including the small airways, and hence, allows the study of several key mechanisms and features of asthma. In line with these char...

Bulletin of the American Meteorological Society, 2021

The Tibetan Plateau, known as the world’s “Third Pole” due to its high altitude, is experiencing ... more The Tibetan Plateau, known as the world’s “Third Pole” due to its high altitude, is experiencing rapid, intense climate change, similar to and even far more than that occurring in the Arctic and Antarctic. Scientific data sharing is very important to address the challenges of better understanding the unprecedented changes in the Third Pole and their impacts on the global environment and humans. The National Tibetan Plateau Data Center (TPDC, http://data.tpdc.ac.cn) is one of the first 20 national data centers endorsed by the Ministry of Science and Technology of China in 2019 and features the most complete scientific data for the Tibetan Plateau and surrounding regions, hosting more than 3,500 datasets in diverse disciplines. Fifty datasets featuring high-mountain observations, land surface parameters, near-surface atmospheric forcing, cryospheric variables, and high-profile article-associated data over the Tibetan Plateau, frequently being used to quantify the hydrological cycle an...

Atmosphere, 2021

The Heihe River Basin (HRB), located on the northeastern edge of the Tibetan Plateau, is the seco... more The Heihe River Basin (HRB), located on the northeastern edge of the Tibetan Plateau, is the second-largest inland river basin in China, with an area of 140,000 km2. The HRB is a coupling area of the westerlies, the Qinghai–Tibet Plateau monsoon and the Southeast monsoon circulation system, and is a relatively independent land-surface water-circulating system. The refined characteristics of moisture recycling over the HRB was described by using the Weather Research and Forecasting (WRF) model for a long-term simulation, and the “finer box model” for calculating the net water-vapor flux. The following conclusions were drawn from the results of this study: (1) The water vapor of the HRB was dominantly transported by the wind from the west and from the north, and the west one was much larger than the north one. The net vapor transported by the west wind was positive, and by the north wind was negative. (2) The precipitation over the HRB was triggered mainly by the vapor from the west, ...

Atmospheric Research, 2021

Abstract This paper aims to test the ability of the WRF-Chem model to simulate sand storms in Nor... more Abstract This paper aims to test the ability of the WRF-Chem model to simulate sand storms in Northwest China and improve the simulation results by introducing remote sensing soil moisture data into WRF-Chem. We conducted sensitivity tests, including parameterization scheme tests and soil moisture tests using WRF-Chem. By comparing various combinations of parameterization schemes, which have considerable impacts on sand emissions, the most suitable parameterization scheme for WRF-Chem to simulate sand storms in Northwest China was selected for establishing models in future research. Based on the optimal combination of parameterization schemes, the sensitivity of sand emissions to soil moisture was tested, indicating that soil moisture has a substantial influence on sand emissions and revealing a nonlinear relationship between sand emissions and soil moisture. Although sand simulations are sensitive to soil moisture, the sand emission volume does not always increase with decreasing soil moisture content. Moreover, the soil moisture content simulated by WRF-Chem is quite different from that observed by satellites. Therefore, we selected ten sand storms that occurred in Northwest China in 2009–2018, including weak, moderate and strong sand storms, to explore the responses of sand storms of different intensities to soil moisture. Some experiments were conducted in two scenarios: scenario A was simulated only by WRF-Chem, and scenario B was designed by replacing the initial soil moisture field in WRF-Chem with soil moisture satellite data from AMSR2 and AMSR-E. Comparing the simulation results with in-situ ground-based and satellite-based measurements indicates that WRF-Chem can capture strong sand storms and some moderate sand storms, but the ability to simulate weak sand storms needs to be greatly improved. After introducing remote sensing soil moisture data into WRF-Chem, the simulation of sand emissions becomes more accurate, substantially improving the simulation results. Among the ten simulated sand storms, the AOD (aerosol optical depth) and PM10 simulation accuracies are improved for five and seven sand storms, respectively. After this improvement, the AOD correlation coefficient can reach 0.63, and the PM10 correlation coefficient can reach 0.60.

Earth and Space Science, 2019

Geophysical Research Letters, 2018

A comprehensive understanding of the regional vegetation responses to long-term climate change wi... more A comprehensive understanding of the regional vegetation responses to long-term climate change will help to forecast Earth system dynamics. Based on a new well-dated pollen data set from Kanas Lake and a review on the published pollen records in and around the Altai Mountains, the regional vegetation dynamics and forcing mechanisms are discussed. In the Altai Mountains, the forest optimum occurred during 10-7ka for the upper forest zone and the tree line decline and/or ecological shifts were caused by climatic cooling from around 7ka. In the lower forest zone, the forest reached an optimum in the middle Holocene, and then increased openness of the forest, possibly caused by both climate cooling and human activities, took place in the late Holocene. In the lower basins or plains around the Altai Mountains, the development of protograssland or forest benefited from increasing humidity in the middle to late Holocene.

Science Bulletin, 2019

Relative sea-level rising and its control strategy in coastal regions of China in the 21st centur... more Relative sea-level rising and its control strategy in coastal regions of China in the 21st century Science in China Series DEarth Sciences 46, 74 (2003); The first mangrove genomes sequenced as the sea level rises

Journal of Geophysical Research: Atmospheres, 2018

Hydrological Processes, 2016

Agricultural and Forest Meteorology, 2017

In this work, we present a strategy for obtaining forest above-ground biomass (AGB) dynamics at a... more In this work, we present a strategy for obtaining forest above-ground biomass (AGB) dynamics at a fine spatial and temporal resolution. Our strategy rests on the assumption that combining estimates of both AGB and carbon fluxes results in a more accurate accounting for biomass than considering the terms separately, since the cumulative carbon flux should be consistent with AGB increments. Such a strategy was successfully applied to the Qilian Mountains, a cold arid region of northwest China. Based on Landsat Thematic Mapper 5 (TM) data and ASTER GDEM V2 products (GDEM), we first improved the efficiency of existing non-parametric methods for mapping regional forest AGB for 2009 by incorporating the Random Forest (RF) model with the k-Nearest Neighbor (k-NN). Validation using forest measurements from 159 plots and the leave-one-out (LOO) method indicated that the estimates were reasonable (R 2 = 0.70 and RMSE = 24.52 tones ha −1). We then obtained one seasonal cycle (2011) of GPP (R 2 = 0.88 and RMSE = 5.02 gC m −2 8d −1) using the MODIS MOD_17 GPP (MOD_17) model that was calibrated to Eddy Covariance (EC) flux tower data (2010). After that, we calibrated the ecological process model (Biome-BioGeochemical Cycles (Biome-BGC)) against above GPP estimates (for 2010) for 30 representative forest plots over an ecological gradient in order to simulate AGB changes over time. Biome-BGC outputs of GPP and net ecosystem exchange (NEE) were validated against EC data (R 2 = 0.75 and RMSE = 1. 27 gC m −2 d −1 for GPP, and R 2 = 0.61 and RMSE = 1.17 gC m −2 d −1 for NEE). The calibrated Biome-BGC was then applied to produce a longer time series for net primary productivity (NPP), which, after conversion into AGB increments according to site-calibrated coefficients, were compared to dendrochronological measurements (R 2 = 0.73 and RMSE = 46.65 g m −2 year −1). By combining these increments with the AGB map of 2009, we were able to model forest AGB dynamics. In the final step, we conducted a Monte Carlo analysis of uncertainties for interannual forest AGB estimates based on errors in the above forest AGB map, NPP estimates, and the conversion of NPP to an AGB increment.

Remote Sensing, 2017

Individually, ground-based, in situ observations, remote sensing, and regional climate modeling c... more Individually, ground-based, in situ observations, remote sensing, and regional climate modeling cannot provide the high-quality precipitation data required for hydrological prediction, especially over complex terrains. Data assimilation techniques can be used to bridge the gap between observations and models by assimilating ground observations and remote sensing products into models to improve precipitation simulation and forecasting. However, only a small portion of satellite-retrieved precipitation products assimilation research has been implemented over complex terrains in an arid region. Here, we used the weather research and forecasting (WRF) model to assimilate two satellite precipitation products (The Tropical Rainfall Measuring Mission: TRMM 3B42 and Fengyun-2D: FY-2D) using the 4D-Var data assimilation method for a typical inland river basin in northwest China's arid region, the Heihe River Basin, where terrains are very complex. The results show that the assimilation of remote sensing precipitation products can improve the initial WRF fields of humidity and temperature, thereby improving precipitation forecasting and decreasing the spin-up time. Hence, assimilating TRMM and FY-2D remote sensing precipitation products using WRF 4D-Var can be viewed as a positive step toward improving the accuracy and lead time of numerical weather prediction models, particularly over regions with complex terrains.

SPIE Proceedings, 2007

The occurrence of landslides generally depends on complex interactions among a large number of pa... more The occurrence of landslides generally depends on complex interactions among a large number of partially interrelated factors. It is appropriate to use multiple regression analysis for predicting landslides from a given set of independent variables. The procedure of landslide hazard assessment by regression analysis, however, requires evaluation of the spatially varying terrain conditions as well as spatial representation of the

Journal of the Japan Landslide Society, 2008

International Journal of Digital Earth, 2011

Sharing of scientific data can help scientific research to flourish and facilitate more widesprea... more Sharing of scientific data can help scientific research to flourish and facilitate more widespread use of scientific data for the benefit of society. The Environmental and Ecological Science Data Center for West China (WestDC), sponsored by the National Natural Science Foundation of China (NSFC), aims to collect, manage, integrate, and disseminate environmental and ecological data from western China. It also aims to provide a long-term data service for multidisciplinary research within NSFC's ''Environment and Ecology of West China Research Plan'' (NSFC West Plan). An integrated platform has been developed by the WestDC, and this has the function of data sharing, acting as a knowledge repository. Major data sets developed by the WestDC include basic geographic data, the regionalization of global data set for China, scientific data for cold and arid regions in China, scientific data for the cryosphere in countries that neighbor China, data relating to the inland river basins in northwestern China, and data submitted by the NSFC West Plan projects. In compliance with the ''full and open'' data sharing policy, most data in the WestDC can be accessed online. Highlights include detailed data documentation, the integration of data with bibliographic knowledge, data publishing, and data reference.

Frontiers of Earth Science, 2012

The spatial resolution of general circulation models (GCMs) is too coarse to represent regional c... more The spatial resolution of general circulation models (GCMs) is too coarse to represent regional climate variations at the regional, basin, and local scales required for many environmental modeling and impact assessments. Weather research and forecasting model (WRF) is a nextgeneration, fully compressible, Euler non-hydrostatic mesoscale forecast model with a run-time hydrostatic option. This model is useful for downscaling weather and climate at the scales from one kilometer to thousands of kilometers, and is useful for deriving meteorological parameters required for hydrological simulation too. The objective of this paper is to validate WRF simulating 5 km/ 1 h air temperatures by daily observed data of China Meteorological Administration (CMA) stations, and by hourly in-situ data of the Watershed Allied Telemetry Experimental Research Project. The daily validation shows that the WRF simulation has good agreement with the observed data; the R 2 between the WRF simulation and each station is more than 0.93; the absolute of meanbias error (MBE) for each station is less than 2°C; and the MBEs of Ejina, Mazongshan and Alxa stations are near zero, with R 2 is more than 0.98, which can be taken as an unbiased estimation. The hourly validation shows that the WRF simulation can capture the basic trend of observed data, the MBE of each site is approximately 2°C, the R 2 of each site is more than 0.80, with the highest at 0.95, and the computed and observed surface air temperature series show a significantly similar trend.

International Journal of Applied Earth Observation and Geoinformation, 2012