Applications of Full Spatial Resolution Space-Based Advanced Infrared Soundings in the Preconvection Environment

Li, Jun; Liu, Chian‐Yi; Zhang, Peng; Schmit, Timothy J.

doi:10.1175/waf-d-10-05057.1

Cited by 33 publications

(28 citation statements)

References 23 publications

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“…The MODIS has 36 spectral channels with wavelengths including the visible, near-infrared, and infrared regions. The MODIS data have been used and their benefits have been demonstrated for environmental applications such as monitoring and predicting weather and climate (e.g., [18][19][20][21]). Abundant MODIS-derived products are available for atmospheric, oceanic, and land applications, among which AOD is the most relevant to air quality studies.…”

Section: Satellite Datamentioning

confidence: 99%

Spatial Correlation of Satellite-Derived PM2.5 with Hospital Admissions for Respiratory Diseases

Liu

Mong

et al. 2016

Remote Sensing

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Abstract:Respiratory diseases, particularly allergic rhinitis, are spatially and temporally correlated with the ground PM 2.5 level. A study of the correlation between the two factors should therefore account for spatiotemporal variations. Satellite observation has the advantage of wide spatial coverage over pin-point style ground-based in situ monitoring stations. Therefore, the current study used both ground measurement and satellite data sets to investigate the spatial and temporal correlation of satellite-derived PM 2.5 with respiratory diseases. This study used 4-year satellite data and PM 2.5 levels of the period at eight stations in Taiwan to obtain the spatial and temporal relationship between aerosol optical depth (AOD) and PM 2.5 . The AOD-PM 2.5 model was further examined using the cross-validation (CV) technique and was found to have high reliability compared with similar models. The model was used to obtain satellite-derived PM 2.5 levels and to analyze the hospital admissions for allergic rhinitis in 2008. The results suggest that adults (18-65 years) and children (3-18 years) are the most vulnerable groups to the effect of PM 2.5 compared with infants and elderly people. This result may be because the two affected age groups spend longer time outdoors. This result may also be attributed to the long-range PM 2.5 transport from upper stream locations and the atmospheric circulation patterns, which are significant in spring and fall. The results of the current study suggest that additional environmental factors that might be associated with respiratory diseases should be considered in future studies.

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Section: Satellite Datamentioning

confidence: 99%

Spatial Correlation of Satellite-Derived PM2.5 with Hospital Admissions for Respiratory Diseases

Liu

Mong

et al. 2016

Remote Sensing

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“…The global training dataset consists of more than 15,000 atmospheric profiles and corresponding to simulate AIRS radiances from the Stand-alone Radiative Transfer Algorithm (SARTA) [23] forward model calculations. The collocated Aqua Moderate Resolution Imaging Spectrometer (MODIS) level 2 cloud mask product (MYD35) was used to determine clear or cloudy AIRS footprint on a SFOV basis [24][25][26]. The selected subset radiances at 1450 AIRS channels were selected in a one-dimensional variational (1DVAR) physical iteration by the conjunction use of SARTA forward calculation.…”

Section: Full-spatial-resolution Airs Sounding Systemmentioning

confidence: 99%

Optimal Use of Space-Borne Advanced Infrared and Microwave Soundings for Regional Numerical Weather Prediction

et al. 2016

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Satellite observations can either be assimilated as radiances or as retrieved physical parameters to reduce error in the initial conditions used by the Numerical Weather Prediction (NWP) model. Assimilation of radiances requires a radiative transfer model to convert atmospheric state in model space to that in radiance space, thus requiring a lot of computational resources especially for hyperspectral instruments with thousands of channels. On the other hand, assimilating the retrieved physical parameters is computationally more efficient as they are already in thermodynamic states, which can be compared with NWP model outputs through the objective analysis scheme. A microwave (MW) sounder and an infrared (IR) sounder have their respective observational limitation due to the characteristics of adopted spectra. The MW sounder observes at much larger field-of-view (FOV) compared to an IR sounder. On the other hand, MW has the capability to reveal the atmospheric sounding when the clouds are presented, but IR observations are highly sensitive to clouds, The advanced IR sounder is able to reduce uncertainties in the retrieved atmospheric temperature and moisture profiles due to its higher spectral-resolution than the MW sounder which has much broader spectra bands. This study tries to quantify the optimal use of soundings retrieved from the microwave sounder AMSU and infrared sounder AIRS onboard the AQUA satellite in the regional Weather and Research Forecasting (WRF) model through three-dimensional variational (3D-var) data assimilation scheme. Four experiments are conducted by assimilating soundings from: (1) clear AIRS single field-of-view (SFOV); (2) retrieved from using clear AMSU and AIRS observations at AMSU field-of-view (SUP); (3) all SFOV soundings within AMSU FOVs must be clear; and (4) SUP soundings which must have all clear SFOV soundings within the AMSU FOV. A baseline experiment assimilating only conventional data is generated for comparison. Various atmospheric state variables at different pressure levels are used to assess the impact from assimilating these different data by comparing them with European Centre for Medium Range Weather Forecast (ECMWF) reanalysis data. Results indicate assimilation of SUP soundings improve the mid and upper troposphere, whereas assimilation of SFOV soundings has positive impact on the lower troposphere. Two additional assimilation experiments are carried out to determine the combination of SUP and SFOV soundings that will provide the best performance throughout the troposphere. The results indicate that optimal combination is to assimilate clear-sky matched IR retrievals with non-matched MW soundings.

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“…The region in question is located within an active cyclogenesis region to the east of the Qinghai-Xizhang Plateau; there are two such places of frequent cyclogenesis, and Zhouqu is within the northern one [e.g., Ding, 1991, p. 203]. In this sense, extreme precipitation at Zhouqu is produced by locally, orographically enhanced convective storms [Li et al, 2012]. In a larger context, the vapor still eventually comes from the Indian Ocean, following a path illustrated in Figure 8.…”

Section: Reproducing the Present August 2010 Zhouqu Landslidementioning

confidence: 99%

The devastating Zhouqu storm‐triggered debris flow of August 2010: Likely causes and possible trends in a future warming climate

Ren

2014

JGR Atmospheres

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On 8 August 2010 in the northwestern Chinese province of Gansu, a rainstorm-triggered debris flow devastated the small county of Zhouqu. A modeling study, using a new multiple-phase scalable and extensible geofluid model, suggests that the cause is an intersection of several events. These were a heavy rainstorm, not necessarily the result of global warming, which triggered the landslide and followed a drought that created surface cracks and crevasses; the geology of the region, notably the loess covering heavily weathered surface rock; and the bedrock damage, that deepened the surface crevasses inflicted by the 7.9 magnitude Wenchuan earthquake of 12 May 2008. Deforestation and topsoil erosion were critical contributors to the massive size of the debris flow. The modeling results underscore the urgency for a high-priority program of revegetation of Zhouqu County, without which the region will remain exposed to future disastrous, "progressive bulking" type landslides. Debris flows are more predictable types of landslides; consequently, a series of "pseudo climate change" model experiments of future extreme precipitation events are carried out using the Weather Research and Forecasting model, forced by temperature perturbations from an ensemble of climate models. In a possibly future warmer climate, extreme precipitation events are anticipated to be more severe, and this study has identified an atmospheric blocking pattern that might produce future extreme precipitation events in the peri-Tibetan Plateau (TP) area (located to the northeast of the TP). Importantly, observations from gravity field measuring satellites indicate that the larger geological environment of this region also is becoming increasingly unstable.

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Applications of Full Spatial Resolution Space-Based Advanced Infrared Soundings in the Preconvection Environment

Cited by 33 publications

References 23 publications

Spatial Correlation of Satellite-Derived PM2.5 with Hospital Admissions for Respiratory Diseases

Spatial Correlation of Satellite-Derived PM2.5 with Hospital Admissions for Respiratory Diseases

Optimal Use of Space-Borne Advanced Infrared and Microwave Soundings for Regional Numerical Weather Prediction

The devastating Zhouqu storm‐triggered debris flow of August 2010: Likely causes and possible trends in a future warming climate

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