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- Author or Editor: Wei Li x
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Abstract
CMIP6 simulations suggest that the probability of the compound hot and dry event occurring in summer 2022 in the Yangtze River basin in China is enhanced by anthropogenic effect by 7 times.
Abstract
CMIP6 simulations suggest that the probability of the compound hot and dry event occurring in summer 2022 in the Yangtze River basin in China is enhanced by anthropogenic effect by 7 times.
Abstract
No Abstract available.
Abstract
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The Qinghai-Xizang (Tibet) Plateau has a profound influence on atmospheric circulation patterns on all time and space scales. This report constitutes a short summary of work being performed at the Lanzhou Institute of Plateau Atmospheric Physics of the Academia Sinica. A short discussion of the climatic characteristics of the plateau is followed by a description of the main features of annual and diurnal cycles in pressure and circulation patterns.
The Qinghai-Xizang (Tibet) Plateau has a profound influence on atmospheric circulation patterns on all time and space scales. This report constitutes a short summary of work being performed at the Lanzhou Institute of Plateau Atmospheric Physics of the Academia Sinica. A short discussion of the climatic characteristics of the plateau is followed by a description of the main features of annual and diurnal cycles in pressure and circulation patterns.
Abstract
The Madden–Julian oscillation (MJO) is the dominant intraseasonal wave phenomenon influencing extreme weather and climate worldwide. Realistic simulations and accurate predictions of MJO genesis are the cornerstones for successfully monitoring, forecasting, and managing meteorological disasters 3–4 weeks in advance. Nevertheless, the genesis processes and emerging precursor signals of an eastward-propagating MJO event remain largely uncertain. Here, we find that the MJO genesis processes observed in the past four decades exhibit remarkable diversity with different seasonality and can be classified objectively into four types, namely, a novel downstream origin from the westward-propagating intraseasonal oscillation (WPISO; 20.4%), localized breeding from the Indian Ocean suppressed convection (IOSC; 15.4%), an upstream succession of the preceding weakly dispersive (WD; 25.9%), and strongly dispersive (SD; 38.3%) MJO. These four types are associated with different oceanic background states, characterized by central Pacific cooling, southern Maritime Continent warming, eastern Pacific cooling, and central Pacific warming for the WPISO, IOSC, WD, and SD types, respectively. The SD type is also favored during the easterly phase of the stratospheric quasi-biennial oscillation. Diverse convective initiations possibly imply various kinds of propagations of MJO. The subseasonal reforecasts indicate robustly distinct prediction skills for the diverse MJO genesis. A window of opportunity for skillful week 3–4 prediction probably opens with the aid of the WPISO-type MJO precursor, which has increased the predictability of primary MJO onset by 1 week. These findings suggest that the diversified MJO genesis can be skillfully foreseen by monitoring unique precursor signals and can also serve as benchmarks for evaluating contemporary models’ modeling and predicting capabilities.
Abstract
The Madden–Julian oscillation (MJO) is the dominant intraseasonal wave phenomenon influencing extreme weather and climate worldwide. Realistic simulations and accurate predictions of MJO genesis are the cornerstones for successfully monitoring, forecasting, and managing meteorological disasters 3–4 weeks in advance. Nevertheless, the genesis processes and emerging precursor signals of an eastward-propagating MJO event remain largely uncertain. Here, we find that the MJO genesis processes observed in the past four decades exhibit remarkable diversity with different seasonality and can be classified objectively into four types, namely, a novel downstream origin from the westward-propagating intraseasonal oscillation (WPISO; 20.4%), localized breeding from the Indian Ocean suppressed convection (IOSC; 15.4%), an upstream succession of the preceding weakly dispersive (WD; 25.9%), and strongly dispersive (SD; 38.3%) MJO. These four types are associated with different oceanic background states, characterized by central Pacific cooling, southern Maritime Continent warming, eastern Pacific cooling, and central Pacific warming for the WPISO, IOSC, WD, and SD types, respectively. The SD type is also favored during the easterly phase of the stratospheric quasi-biennial oscillation. Diverse convective initiations possibly imply various kinds of propagations of MJO. The subseasonal reforecasts indicate robustly distinct prediction skills for the diverse MJO genesis. A window of opportunity for skillful week 3–4 prediction probably opens with the aid of the WPISO-type MJO precursor, which has increased the predictability of primary MJO onset by 1 week. These findings suggest that the diversified MJO genesis can be skillfully foreseen by monitoring unique precursor signals and can also serve as benchmarks for evaluating contemporary models’ modeling and predicting capabilities.
A multiscale modeling framework (MMF), which replaces the conventional cloud parameterizations with a cloud-resolving model (CRM) in each grid column of a GCM, constitutes a new and promising approach for climate modeling. The MMF can provide for global coverage and two-way interactions between the CRMs and their parent GCM. The CRM allows for explicit simulation of cloud processes and their interactions with radiation and surface processes, and the GCM allows for global coverage.
A new MMF has been developed that is based on the NASA Goddard Space Flight Center (GSFC) finite-volume GCM (fvGCM) and the Goddard Cumulus Ensemble (GCE) model. This Goddard MMF produces many features that are similar to another MMF that was developed at Colorado State University (CSU), such as an improved surface precipitation pattern, better cloudiness, improved diurnal variability over both oceans and continents, and a stronger propagating Madden-Julian oscillation (MJO) compared to their parent GCMs using traditional cloud parameterizations. Both MMFs also produce a large and positive precipitation bias in the Indian Ocean and western Pacific during the Northern Hemisphere summer. However, there are also notable differences between the two MMFs. For example, the CSU MMF simulates less rainfall over land than its parent GCM. This is why the CSU MMF simulated less overall global rainfall than its parent GCM. The Goddard MMF simulates more global rainfall than its parent GCM because of the high contribution from the oceanic component. A number of critical issues (i.e., the CRM's physical processes and its configuration) involving the Goddard MMF are discussed in this paper.
A multiscale modeling framework (MMF), which replaces the conventional cloud parameterizations with a cloud-resolving model (CRM) in each grid column of a GCM, constitutes a new and promising approach for climate modeling. The MMF can provide for global coverage and two-way interactions between the CRMs and their parent GCM. The CRM allows for explicit simulation of cloud processes and their interactions with radiation and surface processes, and the GCM allows for global coverage.
A new MMF has been developed that is based on the NASA Goddard Space Flight Center (GSFC) finite-volume GCM (fvGCM) and the Goddard Cumulus Ensemble (GCE) model. This Goddard MMF produces many features that are similar to another MMF that was developed at Colorado State University (CSU), such as an improved surface precipitation pattern, better cloudiness, improved diurnal variability over both oceans and continents, and a stronger propagating Madden-Julian oscillation (MJO) compared to their parent GCMs using traditional cloud parameterizations. Both MMFs also produce a large and positive precipitation bias in the Indian Ocean and western Pacific during the Northern Hemisphere summer. However, there are also notable differences between the two MMFs. For example, the CSU MMF simulates less rainfall over land than its parent GCM. This is why the CSU MMF simulated less overall global rainfall than its parent GCM. The Goddard MMF simulates more global rainfall than its parent GCM because of the high contribution from the oceanic component. A number of critical issues (i.e., the CRM's physical processes and its configuration) involving the Goddard MMF are discussed in this paper.
Abstract
Upper Brahmaputra (UB) is the largest (∼240,000 km2) river basin of the Tibetan Plateau, where hydrological processes are highly sensitive to climate change. However, constrained by difficult access and sparse in situ observations, the variations in precipitation, glaciers, frozen ground, and vegetation across the UB basin remain largely unknown, and consequently the impacts of climate change on streamflow cannot be accurately assessed. To fill this gap, this project aims to establish a basinwide, large-scale observational network (that includes hydrometeorology, glacier, frozen ground, and vegetation observations), which helps quantify the UB runoff processes under climate–cryosphere–vegetation changes. At present, a multisphere observational network has been established throughout the catchment: 1) 12 stations with custom-built weighing automatic rain/snow meters and temperature probes to obtain elevation-dependent gradients; 2) 9 stations with soil moisture/temperature observations at four layers (10, 40, 80, 120 cm) covering Alpine meadow, grasslands, shrub, and forest to measure vegetation (biomass and vegetation types) and soil (physical properties) simultaneously; 3) 34 sets of probes to monitor frozen ground temperatures from 4,500 to 5,200 m elevation (100-m intervals), and two observation systems to monitor water and heat transfer processes in frozen ground at Xuegela (5,278 m) and Mayoumula (5,256 m) Mountains, for improved mapping of permafrost and active layer characteristics; 4) 5 sets of altimetry discharge observations along ungauged cross sections to supplement existing operational gauges; 5) high-precision glacier boundary and ice-surface elevation observations at Namunani Mountain with differential GPS, to supplement existing glacier observations for validating satellite imagery. This network provides an excellent opportunity to monitor UB catchment processes in great detail.
Abstract
Upper Brahmaputra (UB) is the largest (∼240,000 km2) river basin of the Tibetan Plateau, where hydrological processes are highly sensitive to climate change. However, constrained by difficult access and sparse in situ observations, the variations in precipitation, glaciers, frozen ground, and vegetation across the UB basin remain largely unknown, and consequently the impacts of climate change on streamflow cannot be accurately assessed. To fill this gap, this project aims to establish a basinwide, large-scale observational network (that includes hydrometeorology, glacier, frozen ground, and vegetation observations), which helps quantify the UB runoff processes under climate–cryosphere–vegetation changes. At present, a multisphere observational network has been established throughout the catchment: 1) 12 stations with custom-built weighing automatic rain/snow meters and temperature probes to obtain elevation-dependent gradients; 2) 9 stations with soil moisture/temperature observations at four layers (10, 40, 80, 120 cm) covering Alpine meadow, grasslands, shrub, and forest to measure vegetation (biomass and vegetation types) and soil (physical properties) simultaneously; 3) 34 sets of probes to monitor frozen ground temperatures from 4,500 to 5,200 m elevation (100-m intervals), and two observation systems to monitor water and heat transfer processes in frozen ground at Xuegela (5,278 m) and Mayoumula (5,256 m) Mountains, for improved mapping of permafrost and active layer characteristics; 4) 5 sets of altimetry discharge observations along ungauged cross sections to supplement existing operational gauges; 5) high-precision glacier boundary and ice-surface elevation observations at Namunani Mountain with differential GPS, to supplement existing glacier observations for validating satellite imagery. This network provides an excellent opportunity to monitor UB catchment processes in great detail.
In 1997, during the late stages of production of NCEP–NCAR Global Reanalysis (GR), exploration of a regional reanalysis project was suggested by the GR project's Advisory Committee, “particularly if the RDAS [Regional Data Assimilation System] is significantly better than the global reanalysis at capturing the regional hydrological cycle, the diurnal cycle and other important features of weather and climate variability.” Following a 6-yr development and production effort, NCEP's North American Regional Reanalysis (NARR) project was completed in 2004, and data are now available to the scientific community. Along with the use of the NCEP Eta model and its Data Assimilation System (at 32-km–45-layer resolution with 3-hourly output), the hallmarks of the NARR are the incorporation of hourly assimilation of precipitation, which leverages a comprehensive precipitation analysis effort, the use of a recent version of the Noah land surface model, and the use of numerous other datasets that are additional or improved compared to the GR. Following the practice applied to NCEP's GR, the 25-yr NARR retrospective production period (1979–2003) is augmented by the construction and daily execution of a system for near-real-time continuation of the NARR, known as the Regional Climate Data Assimilation System (R-CDAS). Highlights of the NARR results are presented: precipitation over the continental United States (CONUS), which is seen to be very near the ingested analyzed precipitation; fits of tropospheric temperatures and winds to rawinsonde observations; and fits of 2-m temperatures and 10-m winds to surface station observations. The aforementioned fits are compared to those of the NCEP–Department of Energy (DOE) Global Reanalysis (GR2). Not only have the expectations cited above been fully met, but very substantial improvements in the accuracy of temperatures and winds compared to that of GR2 are achieved throughout the troposphere. Finally, the numerous datasets produced are outlined and information is provided on the data archiving and present data availability.
In 1997, during the late stages of production of NCEP–NCAR Global Reanalysis (GR), exploration of a regional reanalysis project was suggested by the GR project's Advisory Committee, “particularly if the RDAS [Regional Data Assimilation System] is significantly better than the global reanalysis at capturing the regional hydrological cycle, the diurnal cycle and other important features of weather and climate variability.” Following a 6-yr development and production effort, NCEP's North American Regional Reanalysis (NARR) project was completed in 2004, and data are now available to the scientific community. Along with the use of the NCEP Eta model and its Data Assimilation System (at 32-km–45-layer resolution with 3-hourly output), the hallmarks of the NARR are the incorporation of hourly assimilation of precipitation, which leverages a comprehensive precipitation analysis effort, the use of a recent version of the Noah land surface model, and the use of numerous other datasets that are additional or improved compared to the GR. Following the practice applied to NCEP's GR, the 25-yr NARR retrospective production period (1979–2003) is augmented by the construction and daily execution of a system for near-real-time continuation of the NARR, known as the Regional Climate Data Assimilation System (R-CDAS). Highlights of the NARR results are presented: precipitation over the continental United States (CONUS), which is seen to be very near the ingested analyzed precipitation; fits of tropospheric temperatures and winds to rawinsonde observations; and fits of 2-m temperatures and 10-m winds to surface station observations. The aforementioned fits are compared to those of the NCEP–Department of Energy (DOE) Global Reanalysis (GR2). Not only have the expectations cited above been fully met, but very substantial improvements in the accuracy of temperatures and winds compared to that of GR2 are achieved throughout the troposphere. Finally, the numerous datasets produced are outlined and information is provided on the data archiving and present data availability.
Abstract
As the second-largest shifting sand desert worldwide, the Taklimakan Desert (TD) represents the typical aeolian landforms in arid regions as an important source of global dust aerosols. It directly affects the ecological environment and human health across East Asia. Thus, establishing a comprehensive environment and climate observation network for field research in the TD region is essential to improve our understanding of the desert meteorology and environment, assess its impact, mitigate potential environmental issues, and promote sustainable development. With a nearly 20-yr effort under the extremely harsh conditions of the TD, the Desert Environment and Climate Observation Network (DECON) has been established completely covering the TD region. The core of DECON is the Tazhong station in the hinterland of the TD. Moreover, the network also includes 4 satellite stations located along the edge of the TD for synergistic observations, and 18 automatic weather stations interspersed between them. Thus, DECON marks a new chapter of environmental and meteorological observation capabilities over the TD, including dust storms, dust emission and transport mechanisms, desert land–atmosphere interactions, desert boundary layer structure, ground calibration for remote sensing monitoring, and desert carbon sinks. In addition, DECON promotes cooperation and communication within the research community in the field of desert environments and climate, which promotes a better understanding of the status and role of desert ecosystems. Finally, DECON is expected to provide the basic support necessary for coordinated environmental and meteorological monitoring and mitigation, joint construction of ecologically friendly communities, and sustainable development of central Asia.
Abstract
As the second-largest shifting sand desert worldwide, the Taklimakan Desert (TD) represents the typical aeolian landforms in arid regions as an important source of global dust aerosols. It directly affects the ecological environment and human health across East Asia. Thus, establishing a comprehensive environment and climate observation network for field research in the TD region is essential to improve our understanding of the desert meteorology and environment, assess its impact, mitigate potential environmental issues, and promote sustainable development. With a nearly 20-yr effort under the extremely harsh conditions of the TD, the Desert Environment and Climate Observation Network (DECON) has been established completely covering the TD region. The core of DECON is the Tazhong station in the hinterland of the TD. Moreover, the network also includes 4 satellite stations located along the edge of the TD for synergistic observations, and 18 automatic weather stations interspersed between them. Thus, DECON marks a new chapter of environmental and meteorological observation capabilities over the TD, including dust storms, dust emission and transport mechanisms, desert land–atmosphere interactions, desert boundary layer structure, ground calibration for remote sensing monitoring, and desert carbon sinks. In addition, DECON promotes cooperation and communication within the research community in the field of desert environments and climate, which promotes a better understanding of the status and role of desert ecosystems. Finally, DECON is expected to provide the basic support necessary for coordinated environmental and meteorological monitoring and mitigation, joint construction of ecologically friendly communities, and sustainable development of central Asia.
