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Before and during the 2008 Beijing Olympics from June to September, ground-based and satellite monitoring were carried out over Beijing and its vicinity (BIV) in a campaign to quantify the outcomes of various emission control measures. These include hourly surface PM10 and PM2.5 and their fraction of black carbon (BC), organics, nitrate, sulfate, ammonium, and daily aerosol optical depth (AOD), together with hourly reactive gases, surface ozone, and daily columnar NO2 from satellite. The analyses, excluding the estimates from weather contributions, demonstrate that after the control measures, including banning ~300,000 “yellow-tag” vehicles from roads, the even–odd turn of motor vehicles on the roads, and emission reduction aiming at coal combustion, were implemented, air quality in Beijing improved substantially. The levels of NO, NO2, NOx, CO, SO2, BC, organics, and nitrate dropped by about 30%–60% and the ozone moderately increased by ~40% while the sulfate and ammonium exhibited different patterns during various control stages. Weather conditions have a great impact on the summertime secondary aerosol (~80% of total PM) and O3 formations over BIV. During the Olympic Game period, various atmospheric components decreased dramatically at Beijing compared to the same period in the previous years. This decrease was related not only to the implementation of rigorous control measures, but also to the favorable weather processes. The subtropical high was located to the south so that Beijing's weather was dominated by the interaction between a frequently eastward shifting trough in the westerlies and a cold continental high with clear to cloudy days or showery weather.
Before and during the 2008 Beijing Olympics from June to September, ground-based and satellite monitoring were carried out over Beijing and its vicinity (BIV) in a campaign to quantify the outcomes of various emission control measures. These include hourly surface PM10 and PM2.5 and their fraction of black carbon (BC), organics, nitrate, sulfate, ammonium, and daily aerosol optical depth (AOD), together with hourly reactive gases, surface ozone, and daily columnar NO2 from satellite. The analyses, excluding the estimates from weather contributions, demonstrate that after the control measures, including banning ~300,000 “yellow-tag” vehicles from roads, the even–odd turn of motor vehicles on the roads, and emission reduction aiming at coal combustion, were implemented, air quality in Beijing improved substantially. The levels of NO, NO2, NOx, CO, SO2, BC, organics, and nitrate dropped by about 30%–60% and the ozone moderately increased by ~40% while the sulfate and ammonium exhibited different patterns during various control stages. Weather conditions have a great impact on the summertime secondary aerosol (~80% of total PM) and O3 formations over BIV. During the Olympic Game period, various atmospheric components decreased dramatically at Beijing compared to the same period in the previous years. This decrease was related not only to the implementation of rigorous control measures, but also to the favorable weather processes. The subtropical high was located to the south so that Beijing's weather was dominated by the interaction between a frequently eastward shifting trough in the westerlies and a cold continental high with clear to cloudy days or showery weather.
The very limited instrumental record makes extensive analyses of the natural variability of global tropical cyclone activities difficult in most of the tropical cyclone basins. However, in the two regions where reasonably reliable records exist (the North Atlantic and the western North Pacific), substantial multidecadal variability (particularly for intense Atlantic hurricanes) is found, but there is no clear evidence of long-term trends. Efforts have been initiated to use geological and geomorphological records and analysis of oxygen isotope ratios in rainfall recorded in cave stalactites to establish a paleoclimate of tropical cyclones, but these have not yet produced definitive results. Recent thermodynamical estimation of the maximum potential intensities (MPI) of tropical cyclones shows good agreement with observations.
Although there are some uncertainties in these MPI approaches, such as their sensitivity to variations in parameters and failure to include some potentially important interactions such as ocean spray feedbacks, the response of upper-oceanic thermal structure, and eye and eyewall dynamics, they do appear to be an objective tool with which to predict present and future maxima of tropical cyclone intensity. Recent studies indicate the MPI of cyclones will remain the same or undergo a modest increase of up to 10%–20%. These predicted changes are small compared with the observed natural variations and fall within the uncertainty range in current studies. Furthermore, the known omissions (ocean spray, momentum restriction, and possibly also surface to 300-hPa lapse rate changes) could all operate to mitigate the predicted intensification.
A strong caveat must be placed on analysis of results from current GCM simulations of the “tropical-cyclone-like” vortices. Their realism, and hence prediction skill (and also that of “embedded” mesoscale models), is greatly limited by the coarse resolution of current GCMs and the failure to capture environmental factors that govern cyclone intensity. Little, therefore, can be said about the potential changes of the distribution of intensities as opposed to maximum achievable intensity. Current knowledge and available techniques are too rudimentary for quantitative indications of potential changes in tropical cyclone frequency.
The broad geographic regions of cyclogenesis and therefore also the regions affected by tropical cyclones are not expected to change significantly. It is emphasized that the popular belief that the region of cyclogenesis will expand with the 26°C SST isotherm is a fallacy. The very modest available evidence points to an expectation of little or no change in global frequency. Regional and local frequencies could change substantially in either direction, because of the dependence of cyclone genesis and track on other phenomena (e.g., ENSO) that are not yet predictable. Greatly improved skills from coupled global ocean–atmosphere models are required before improved predictions are possible.
The very limited instrumental record makes extensive analyses of the natural variability of global tropical cyclone activities difficult in most of the tropical cyclone basins. However, in the two regions where reasonably reliable records exist (the North Atlantic and the western North Pacific), substantial multidecadal variability (particularly for intense Atlantic hurricanes) is found, but there is no clear evidence of long-term trends. Efforts have been initiated to use geological and geomorphological records and analysis of oxygen isotope ratios in rainfall recorded in cave stalactites to establish a paleoclimate of tropical cyclones, but these have not yet produced definitive results. Recent thermodynamical estimation of the maximum potential intensities (MPI) of tropical cyclones shows good agreement with observations.
Although there are some uncertainties in these MPI approaches, such as their sensitivity to variations in parameters and failure to include some potentially important interactions such as ocean spray feedbacks, the response of upper-oceanic thermal structure, and eye and eyewall dynamics, they do appear to be an objective tool with which to predict present and future maxima of tropical cyclone intensity. Recent studies indicate the MPI of cyclones will remain the same or undergo a modest increase of up to 10%–20%. These predicted changes are small compared with the observed natural variations and fall within the uncertainty range in current studies. Furthermore, the known omissions (ocean spray, momentum restriction, and possibly also surface to 300-hPa lapse rate changes) could all operate to mitigate the predicted intensification.
A strong caveat must be placed on analysis of results from current GCM simulations of the “tropical-cyclone-like” vortices. Their realism, and hence prediction skill (and also that of “embedded” mesoscale models), is greatly limited by the coarse resolution of current GCMs and the failure to capture environmental factors that govern cyclone intensity. Little, therefore, can be said about the potential changes of the distribution of intensities as opposed to maximum achievable intensity. Current knowledge and available techniques are too rudimentary for quantitative indications of potential changes in tropical cyclone frequency.
The broad geographic regions of cyclogenesis and therefore also the regions affected by tropical cyclones are not expected to change significantly. It is emphasized that the popular belief that the region of cyclogenesis will expand with the 26°C SST isotherm is a fallacy. The very modest available evidence points to an expectation of little or no change in global frequency. Regional and local frequencies could change substantially in either direction, because of the dependence of cyclone genesis and track on other phenomena (e.g., ENSO) that are not yet predictable. Greatly improved skills from coupled global ocean–atmosphere models are required before improved predictions are possible.
This paper describes the optimal design and its research-to-operation transition of an integrated global observing system of satellites and in situ observations. The integrated observing system is used for climate assessment using sea surface temperature (SST). Satellite observations provide superior samplings while in situ observations provide the ground truth. Observing System Simulation Experiments (OSSEs) were used to objectively design an efficient in situ system to reduce satellite biases to a required accuracy. The system design was peer reviewed and was then transitioned into operations as a U.S. contribution to the international Global Climate Observing System (GCOS). A system performance measure was also formulated and operationally tracked under the Government Performance Results Act (GPRA). Additional OSSEs assisted the planning, programming, budgeting, and execution system at the National Oceanic and Atmospheric Administration (NOAA) to maximize design efficiency. This process of research to operation and decision making enables NOAA to strategically target its observing system investments. The principles of this specific example may have potential applicability to the other components of GCOS.
This paper describes the optimal design and its research-to-operation transition of an integrated global observing system of satellites and in situ observations. The integrated observing system is used for climate assessment using sea surface temperature (SST). Satellite observations provide superior samplings while in situ observations provide the ground truth. Observing System Simulation Experiments (OSSEs) were used to objectively design an efficient in situ system to reduce satellite biases to a required accuracy. The system design was peer reviewed and was then transitioned into operations as a U.S. contribution to the international Global Climate Observing System (GCOS). A system performance measure was also formulated and operationally tracked under the Government Performance Results Act (GPRA). Additional OSSEs assisted the planning, programming, budgeting, and execution system at the National Oceanic and Atmospheric Administration (NOAA) to maximize design efficiency. This process of research to operation and decision making enables NOAA to strategically target its observing system investments. The principles of this specific example may have potential applicability to the other components of GCOS.
Abstract
The NOAA Science Advisory Board appointed a task force to prepare a white paper on the use of observing system simulation experiments (OSSEs). Considering the importance and timeliness of this topic and based on this white paper, here we briefly review the use of OSSEs in the United States, discuss their values and limitations, and develop five recommendations for moving forward: national coordination of relevant research efforts, acceleration of OSSE development for Earth system models, consideration of the potential impact on OSSEs of deficiencies in the current data assimilation and prediction system, innovative and new applications of OSSEs, and extension of OSSEs to societal impacts. OSSEs can be complemented by calculations of forecast sensitivity to observations, which simultaneously evaluate the impact of different observation types in a forecast model system.
Abstract
The NOAA Science Advisory Board appointed a task force to prepare a white paper on the use of observing system simulation experiments (OSSEs). Considering the importance and timeliness of this topic and based on this white paper, here we briefly review the use of OSSEs in the United States, discuss their values and limitations, and develop five recommendations for moving forward: national coordination of relevant research efforts, acceleration of OSSE development for Earth system models, consideration of the potential impact on OSSEs of deficiencies in the current data assimilation and prediction system, innovative and new applications of OSSEs, and extension of OSSEs to societal impacts. OSSEs can be complemented by calculations of forecast sensitivity to observations, which simultaneously evaluate the impact of different observation types in a forecast model system.
Errors in the simulation of clouds in general circulation models (GCMs) remain a long-standing issue in climate projections, as discussed in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. This highlights the need for developing new analysis techniques to improve our knowledge of the physical processes at the root of these errors. The Cloud Feedback Model Intercomparison Project (CFMIP) pursues this objective, and under that framework the CFMIP Observation Simulator Package (COSP) has been developed. COSP is a flexible software tool that enables the simulation of several satellite-borne active and passive sensor observations from model variables. The flexibility of COSP and a common interface for all sensors facilitates its use in any type of numerical model, from high-resolution cloud-resolving models to the coarser-resolution GCMs assessed by the IPCC, and the scales in between used in weather forecast and regional models. The diversity of model parameterization techniques makes the comparison between model and observations difficult, as some parameterized variables (e.g., cloud fraction) do not have the same meaning in all models. The approach followed in COSP permits models to be evaluated against observations and compared against each other in a more consistent manner. This permits a more detailed diagnosis of the physical processes that govern the behavior of clouds and precipitation in numerical models. The World Climate Research Programme (WCRP) Working Group on Coupled Modelling has recommended the use of COSP in a subset of climate experiments that will be assessed by the next IPCC report. In this article we describe COSP, present some results from its application to numerical models, and discuss future work that will expand its capabilities.
Errors in the simulation of clouds in general circulation models (GCMs) remain a long-standing issue in climate projections, as discussed in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. This highlights the need for developing new analysis techniques to improve our knowledge of the physical processes at the root of these errors. The Cloud Feedback Model Intercomparison Project (CFMIP) pursues this objective, and under that framework the CFMIP Observation Simulator Package (COSP) has been developed. COSP is a flexible software tool that enables the simulation of several satellite-borne active and passive sensor observations from model variables. The flexibility of COSP and a common interface for all sensors facilitates its use in any type of numerical model, from high-resolution cloud-resolving models to the coarser-resolution GCMs assessed by the IPCC, and the scales in between used in weather forecast and regional models. The diversity of model parameterization techniques makes the comparison between model and observations difficult, as some parameterized variables (e.g., cloud fraction) do not have the same meaning in all models. The approach followed in COSP permits models to be evaluated against observations and compared against each other in a more consistent manner. This permits a more detailed diagnosis of the physical processes that govern the behavior of clouds and precipitation in numerical models. The World Climate Research Programme (WCRP) Working Group on Coupled Modelling has recommended the use of COSP in a subset of climate experiments that will be assessed by the next IPCC report. In this article we describe COSP, present some results from its application to numerical models, and discuss future work that will expand its capabilities.
Abstract
During the presummer rainy season (April–June), southern China often experiences frequent occurrences of extreme rainfall, leading to severe flooding and inundations. To expedite the efforts in improving the quantitative precipitation forecast (QPF) of the presummer rainy season rainfall, the China Meteorological Administration (CMA) initiated a nationally coordinated research project, namely, the Southern China Monsoon Rainfall Experiment (SCMREX) that was endorsed by the World Meteorological Organization (WMO) as a research and development project (RDP) of the World Weather Research Programme (WWRP). The SCMREX RDP (2013–18) consists of four major components: field campaign, database management, studies on physical mechanisms of heavy rainfall events, and convection-permitting numerical experiments including impact of data assimilation, evaluation/improvement of model physics, and ensemble prediction. The pilot field campaigns were carried out from early May to mid-June of 2013–15. This paper: i) describes the scientific objectives, pilot field campaigns, and data sharing of SCMREX; ii) provides an overview of heavy rainfall events during the SCMREX-2014 intensive observing period; and iii) presents examples of preliminary research results and explains future research opportunities.
Abstract
During the presummer rainy season (April–June), southern China often experiences frequent occurrences of extreme rainfall, leading to severe flooding and inundations. To expedite the efforts in improving the quantitative precipitation forecast (QPF) of the presummer rainy season rainfall, the China Meteorological Administration (CMA) initiated a nationally coordinated research project, namely, the Southern China Monsoon Rainfall Experiment (SCMREX) that was endorsed by the World Meteorological Organization (WMO) as a research and development project (RDP) of the World Weather Research Programme (WWRP). The SCMREX RDP (2013–18) consists of four major components: field campaign, database management, studies on physical mechanisms of heavy rainfall events, and convection-permitting numerical experiments including impact of data assimilation, evaluation/improvement of model physics, and ensemble prediction. The pilot field campaigns were carried out from early May to mid-June of 2013–15. This paper: i) describes the scientific objectives, pilot field campaigns, and data sharing of SCMREX; ii) provides an overview of heavy rainfall events during the SCMREX-2014 intensive observing period; and iii) presents examples of preliminary research results and explains future research opportunities.
Abstract
Unique data from seven flights of the Coyote small unmanned aircraft system (sUAS) were collected in Hurricanes Maria (2017) and Michael (2018). Using NOAA’s P-3 reconnaissance aircraft as a deployment vehicle, the sUAS collected high-frequency (>1 Hz) measurements in the turbulent boundary layer of hurricane eyewalls, including measurements of wind speed, wind direction, pressure, temperature, moisture, and sea surface temperature, which are valuable for advancing knowledge of hurricane structure and the process of hurricane intensification. This study presents an overview of the sUAS system and preliminary analyses that were enabled by these unique data. Among the most notable results are measurements of turbulence kinetic energy and momentum flux for the first time at low levels (<150 m) in a hurricane eyewall. At higher altitudes and lower wind speeds, where data were collected from previous flights of the NOAA P-3, the Coyote sUAS momentum flux values are encouragingly similar, thus demonstrating the ability of an sUAS to measure important turbulence properties in hurricane boundary layers. Analyses from a large-eddy simulation (LES) are used to place the Coyote measurements into context of the complicated high-wind eyewall region. Thermodynamic data are also used to evaluate the operational HWRF model, showing a cool, dry, and thermodynamically unstable bias near the surface. Preliminary data assimilation experiments also show how sUAS data can be used to improve analyses of storm structure. These results highlight the potential of sUAS operations in hurricanes and suggest opportunities for future work using these promising new observing platforms.
Abstract
Unique data from seven flights of the Coyote small unmanned aircraft system (sUAS) were collected in Hurricanes Maria (2017) and Michael (2018). Using NOAA’s P-3 reconnaissance aircraft as a deployment vehicle, the sUAS collected high-frequency (>1 Hz) measurements in the turbulent boundary layer of hurricane eyewalls, including measurements of wind speed, wind direction, pressure, temperature, moisture, and sea surface temperature, which are valuable for advancing knowledge of hurricane structure and the process of hurricane intensification. This study presents an overview of the sUAS system and preliminary analyses that were enabled by these unique data. Among the most notable results are measurements of turbulence kinetic energy and momentum flux for the first time at low levels (<150 m) in a hurricane eyewall. At higher altitudes and lower wind speeds, where data were collected from previous flights of the NOAA P-3, the Coyote sUAS momentum flux values are encouragingly similar, thus demonstrating the ability of an sUAS to measure important turbulence properties in hurricane boundary layers. Analyses from a large-eddy simulation (LES) are used to place the Coyote measurements into context of the complicated high-wind eyewall region. Thermodynamic data are also used to evaluate the operational HWRF model, showing a cool, dry, and thermodynamically unstable bias near the surface. Preliminary data assimilation experiments also show how sUAS data can be used to improve analyses of storm structure. These results highlight the potential of sUAS operations in hurricanes and suggest opportunities for future work using these promising new observing platforms.
Aerosol- and moonsoon-related droughts and floods are two of the most serious environmental hazards confronting more than 60% of the population of the world living in the Asian monsoon countries. In recent years, thanks to improved satellite and in situ observations, and better models, great strides have been made in aerosol and monsoon research, respectively. There is now a growing body of evidence suggesting that interaction of aerosol forcing with monsoon dynamics may alter the redistribution of energy in the atmosphere and at the Earth s surface, thereby influencing monsoon water cycle and climate. In this article, the authors describe the scientific rationale and challenges for an integrated approach to study the interactions between aerosol and monsoon water cycle dynamics. A Joint Aerosol-Monsoon Experiment (JAMEX) is proposed for 2007–11, with enhanced observations of the physical and chemical properties, sources and sinks, and long-range transport of aerosols, in conjunction with meteorological and oceanographic observations in the Indo-Pacific continental and oceanic regions. JAMEX will leverage on coordination among many ongoing and planned national research programs on aerosols and monsoons in China, India, Japan, Nepal, Italy, and the United States, as well as international research programs of the World Climate Research Program (WCRP) and the World Meteorological Organization (WMO).
Aerosol- and moonsoon-related droughts and floods are two of the most serious environmental hazards confronting more than 60% of the population of the world living in the Asian monsoon countries. In recent years, thanks to improved satellite and in situ observations, and better models, great strides have been made in aerosol and monsoon research, respectively. There is now a growing body of evidence suggesting that interaction of aerosol forcing with monsoon dynamics may alter the redistribution of energy in the atmosphere and at the Earth s surface, thereby influencing monsoon water cycle and climate. In this article, the authors describe the scientific rationale and challenges for an integrated approach to study the interactions between aerosol and monsoon water cycle dynamics. A Joint Aerosol-Monsoon Experiment (JAMEX) is proposed for 2007–11, with enhanced observations of the physical and chemical properties, sources and sinks, and long-range transport of aerosols, in conjunction with meteorological and oceanographic observations in the Indo-Pacific continental and oceanic regions. JAMEX will leverage on coordination among many ongoing and planned national research programs on aerosols and monsoons in China, India, Japan, Nepal, Italy, and the United States, as well as international research programs of the World Climate Research Program (WCRP) and the World Meteorological Organization (WMO).
