The Application of ARGO Data to the Global Ocean Data Assimilation Operational System of NCC

1. Introduction It is well-known that the state of ocean plays very important role in the climate change. But there is a paucity of the ocean observation data. The data distri- bution in the space, time and different components is very inhomogeneous, even in some areas, there are no any observation data. Hence, it brings some diffcul- ties to the scientists to study many problems relevant to ocean. This situation has been being changed since ARGO (Array for Real-time Geostrophic Oceanogra-…     

The Fractal Dimension Distribution of the Short-Term Climate System in China and It’s Connection with the Monsoon Climate

By analyzing the Fractal Dimension(FD) distribution of the Short-range Climate system(SCS) in China, it is found that the FD varies in different region and this just agrees with the regionally of the monsoon climate in China. The FD of the SCS Lays between 2.0 and 5.0. In the vast eastern area of China, the FD almost grows gradually with the latitude. Line 4.0 is along the mountain chains from the Nanlin Mountain to the Wuyi Mountain. North of the line the FD varies only slightly and all are above 4.0. Only in coastal islands the FD is smaller than 3.0.     

Impacts of XBT, TAO, Altimetry and ARGO Observations on the Tropical Pacific Ocean Data Assimilation

This study aims at assessing the relative impacts of four major components of the tropical Pacific Ocean observing system on assimilation of temperature and salinity fields. Observations were collected over a period between January 2001 through June 2003 including temperature data from the expendable bathythermographs （XBT）, thermistor data from the Tropical Ocean Global Atmosphere Tropical Atmosphere-Ocean （TOGA-TAO） mooring array, sea level anomalies from the Topex/Poseidon and Jason-1 altimetry （T/P-J）, and temperature and salinity profiles from the Array for Real-time Geostrophic Oceanography （ARGO） floats. An efficient three-dimensional variational analysis-based method was introduced to assimilate the above data into the tropical-Pacific circulation model. To evaluate the impact of the individual component of the observing system, four observation system experiments were carried out. The experiment that assimilated all four components of the observing system was taken as the reference. The other three experiments were implemented by withholding one of the four components. Results show that the spatial distribution of the data influences its relative contribution. XBT observations produce the most distinguished effects on temperature analyses in the off-equatorial region due to the large amount of measurements and high quality. Similarly, the impact of TAO is dominant in the equatorial region due to the focus of the spatial distribution. The Topex/Poseidon-Jason-1 can be highly complementary where the XBT and TAO observations are sparse. The contribution of XBT or TAO on the assimilated salinity is made by the model dynamics because no salinity observations from them are assimilated. Therefore, T/P-J, as a main source for providing salinity data, has been shown to have greater impacts than either XBT or TAO on the salinity analysis. Although ARGO includes the subsurface observations, the relatively smaller number of observation makes it have the smallest contribution to the assimilation syst     

Study on the Variational Assimilation Technique for the Retrieval of Wind Fields from Doppler Radar Data

This paper introduces a variational assimilation technique for the retrieval of wind fields from Doppler radar data. The assimilated information included both the radial velocity (RV) and the movement of radar echo. In this assimilation technique, the key is transforming the movement of radar echo to a new radar measuring variable- "apparent velocity" (AV). Thus, the information of wind is added, and the indeterminacy of recovering two-dimensional wind only by AV was overcome effectively by combining RV with AV. By means of CMA GRAPES-3Dvar and CINRAD data, some experiments were performed. The results show that the method of retrieval of wind fields is useful in obtaining the construction of the weather system.     

An Examination of ENSO’s Effect on the Monthly and Seasonal Climate of Hong Kong from a Statistical Perspective

This study aims to examine the effect of El Nino and La Nina on the monthly and seasonal climate of Hong Kong against the ENSO-neutral situation from a statistical perspective. Monthly and seasonal temperature and rainfall of Hong Kong and monthly number of tropical cyclones (TCs) coming within 500 km of the city over the 59-yr (1950-2008) period are examined under three ENSO situations, namely El Nino, La Nina, and ENSO-neutral. It is found that, compared with the ENSO-neutral situation, El Nino tends...     

Climate displacement and resettlement: the importance of claims-making ‘from below’

Climate-induced population displacement and resettlement is an ongoing problem around the world, and one that is being exacerbated by climate change. To date, most attempts to address this problem have taken a top-down approach in which international justice, legal and humanitarian frameworks are extended ‘downwards’ by policymakers and governments to local populations. However, there has been limited systematic work that emphasizes the abilities of affected peoples themselves to develop and formulate their own justice-based solutions. This paper presents an analytical framework for thinking about ‘bottom-up’ claims-making that emphasizes naming, blaming, claiming and framing. The framework enables claims-making to be distinguished from other forms of community-based agency, such as adaptation. The paper also suggests a normative framework to support policymakers and practitioners in helping communities facing displacement to make claims. The normative framework focuses on the barriers to, and opportunities for, claims-making ‘from below’.     

Climate change and the long-term viability of the World’s busiest heavy haul ice road

Theoretical and Applied Climatology - Climate models project that the northern high latitudes will warm at a rate in excess of the global mean. This will pose severe problems for Arctic and...     

Variability of CO2 fugacity at the western edge of the tropical Atlantic Ocean from the 8°N to 38°W PIRATA buoy

Hourly data of CO₂ fugacity (fCO₂) at 8°N–38°W were analyzed from 2008 to 2011. Analyses of wind, rainfall, temperature and salinity data from the buoy indicated two distinct seasonal periods. The first period (January to July) had a mean fCO₂ of 378.9 μatm (n = 7512). During this period, in which the study area was characterized by small salinity variations, the fCO₂ is mainly controlled by sea surface temperature (SST) variations (fCO₂ = 24.4*SST-281.1, r² = 0.8). During the second period (August–December), the mean fCO₂ was 421.9 μatm (n = 11571). During these months, the region is subjected to the simultaneous action of (a) rainfall induced by the presence of the Intertropical Convergence Zone (ITCZ); (b) arrival of fresh water from the Amazon River plume that is transported to the east by the North Equatorial Countercurrent (NECC) after the retroflection of the North Brazil Current (NBC); and (c) vertical input of CO₂-rich water due to Ekman pumping. The data indicated the existence of high-frequency fCO₂ variability (periods less than 24 h). This high variability is related to two different mechanisms. In the first mechanism, fCO₂ increases are associated to rapid increases in SST and are attributed to the diurnal cycle of solar radiation. In addition, low wind speed contributes to SST rising by inhibiting vertical mixing. In the second mechanism, fCO₂ decreases are associated to SSS decreases caused by heavy rainfall.     

An Introduction to the Integrated Climate Model of the Center for Monsoon System Research and Its Simulated Influence of El Ni?no on East Asian–Western North Pacific Climate

This study introduces a new global climate model—the Integrated Climate Model(ICM)—developed for the seasonal prediction of East Asian–western North Pacific(EA–WNP) climate by the Center for Monsoon System Research at the Institute of Atmospheric Physics(CMSR, IAP), Chinese Academy of Sciences. ICM integrates ECHAM5 and NEMO2.3 as its atmospheric and oceanic components, respectively, using OASIS3 as the coupler. The simulation skill of ICM is evaluated here, including the simulated climatology, interannual variation, and the influence of El Nińo as one of the most important factors on EA–WNP climate. ICM successfully reproduces the distribution of sea surface temperature(SST) and precipitation without climate shift, the seasonal cycle of equatorial Pacific SST, and the precipitation and circulation of East Asian summer monsoon. The most prominent biases of ICM are the excessive cold tongue and unrealistic westward phase propagation of equatorial Pacific SST. The main interannual variation of the tropical Pacific SST and EA–WNP climate—El Nińo and the East Asia–Pacific Pattern—are also well simulated in ICM, with realistic spatial pattern and period. The simulated El Nińo has significant impact on EA–WNP climate, as in other models. The assessment shows ICM should be a reliable model for the seasonal prediction of EA–WNP climate.     

The AVOID programme’s new simulations of the global benefits of stringent climate change mitigation

Quantitative simulations of the global-scale benefits of climate change mitigation are presented, using a harmonised, self-consistent approach based on a single set of climate change scenarios. The approach draws on a synthesis of output from both physically-based and economics-based models, and incorporates uncertainty analyses. Previous studies have projected global and regional climate change and its impacts over the 21st century but have generally focused on analysis of business-as-usual scenarios, with no explicit mitigation policy included. This study finds that both the economics-based and physically-based models indicate that early, stringent mitigation would avoid a large proportion of the impacts of climate change projected for the 2080s. However, it also shows that not all the impacts can now be avoided, so that adaptation would also therefore be needed to avoid some of the potential damage. Delay in mitigation substantially reduces the percentage of impacts that can be avoided, providing strong new quantitative evidence for the need for stringent and prompt global mitigation action on greenhouse gas emissions, combined with effective adaptation, if large, widespread climate change impacts are to be avoided. Energy technology models suggest that such stringent and prompt mitigation action is technologically feasible, although the estimated costs vary depending on the specific modelling approach and assumptions.     

Uncertainty of the numerical solution of a nonlinear system’s long-term behavior and global convergence of the numerical pattern

The computational uncertainty principle in nonlinear ordinary differential equations makes the numerical solution of the long-term behavior of nonlinear atmospheric equations have no meaning. The main reason is that, in the error analysis theory of present-day computational mathematics, the non-linear process between truncation error and rounding erroris treated as a linear operation. In this paper, based on the operator equations of large-scale atmospheric movement, the above limitation is overcome by using the notion of cell mapping. Through studying the global asymptotic characteristics of the numerical pattern of the large-scale atmospheric equations, the definitions of the global convergence and an appropriate discrete algorithm of the numerical pattern are put forward. Three determinant theorems about the global convergence of the numerical pattern are presented, which provide the theoretical basis for constructing the globally convergent numerical pattern. Further, it is pointed out that only a globally convergent numerical pattern can improve the veracity of climatic prediction.     

Planetary-Scale Wave Structures of the Earth’s Atmosphere Revealed from the COSMIC Observations

GPS radio occultation（GPS RO） method,an active satellite-to-satellite remote sensing technique,is capable of producing accurate,all-weather,round the clock,global refractive index,density,pressure,and temperature profiles of the troposphere and stratosphere.This study presents planetary-scale equatorially trapped Kelvin waves in temperature profiles retrieved using COSMIC（Constellation Observing System for Meteorology,Ionosphere,and Climate） satellites during 2006-2009 and their interactions with background atmospheric conditions.It is found that the Kelvin waves are not only associated with wave periods of higher than 10 days（slow Kelvin waves） with higher zonal wave numbers（either 1 or 2）,but also possessing downward phase progression,giving evidence that the source regions of them are located at lower altitudes.A thorough verification of outgoing longwave radiation（OLR） reveals that deep convection activity has developed regularly over the Indonesian region,suggesting that the Kelvin waves are driven by the convective activity.The derived Kelvin waves show enhanced（diminished） tendencies during westward（eastward） phase of the quasi-biennial oscillation（QBO） in zonal winds,implying a mutual relation between both of them.The El Nino and Southern Oscillation（ENSO） below 18 km and the QBO features between 18 and 27km in temperature profiles are observed during May 2006-May 2010 with the help of an adaptive data analysis technique known as Hilbert Huang Transform（HHT）.Further,temperature anomalies computed using COSMIC retrieved temperatures are critically evaluated during different phases of ENSO,which has revealed interesting results and are discussed in light of available literature.     

Climate Change driven evolution of hazards to Europe’s transport infrastructure throughout the twenty-first century

Air circulation due to the urban heat island (UHI) effect can influence the dispersion of air pollutants in a metropolis. This study focusses on the influence of the UHI effect on particulate matter (PM; including PM_2.5 and PM_2.5–10) between May and September 2010–2012 in the Taipei basin. Meteorological and PM data were obtained from the sites, owned by the governmental authorities. The analysis was carried out using t test, relative indices (RIs), Pearson product–moment correlation and stepwise regression. The results show that the RI values for PM were the highest at moderate UHI intensity (MUI; 2 °C ≤ UHI < 4 °C) rather than at strong UHI intensity (SUI; 4 °C ≤ UHI) during the peak time for anthropogenic emissions (20:00 LST). Neither the accumulation of PM nor the surface convergence occurred in the hot centre, as shown by the case study. At MUI, more than 89 % of the synoptic weather patterns showed that the weather was clear and hot or that the atmosphere was stable. The variation in PM was associated with horizontal and vertical air dispersion. Poor horizontal air dispersion, with subsidence, caused an increase in PM at MUI. However, the updraft motion diluted the PM at SUI. The stepwise regression models show that the cloud index and surface air pressure determined the variation in PM_2.5–10, while cloud index, wind speed and mixing height influenced the variation in PM_2.5. In conclusion, a direct relationship between UHI effect and PM was not obvious.     

An Introduction to the Integrated Climate Model of the Center for Monsoon System Research and its simulated influence of El Niño on East Asian-western North Pacific climate

This study introduces a new global climate model--the Integrated Climate Model （ICM）--developed for the seasonal prediction of East Asian-western North Pacific （EA-WNP） climate by the Center for Monsoon System Research at the Institute of Atmospheric Physics （CMSR, IAP）, Chinese Academy of Sciences. ICM integrates ECHAM5 and NEMO2.3 as its atmospheric and oceanic components, respectively, using OASIS3 as the coupler. The simulation skill of ICM is evaluated here, including the simulated climatology, interannual variation, and the influence of E1 Nifio as one of the most important factors on EA-WNP climate. ICM successfully reproduces the distribution of sea surface temperature （SST） and precipitation without climate shift, the seasonal cycle of equatorial Pacific SST, and the precipitation and circulation of East Asian summer monsoon. The most prominent biases of ICM are the excessive cold tongue and unrealistic westward phase propagation of equatorial Pacific SST. The main interannual variation of the tropical Pacific SST and EA-WNP climate E1 Nifio and the East Asia-Pacific Pattern--are also well simulated in ICM, with realistic spatial pattern and period. The simulated E1 Nifio has significant impact on EA-WNP climate, as in other models. The assessment shows ICM should be a reliable model for the seasonal prediction of EA-WNP climate.     

Assimilation of Radar and Cloud-to-Ground Lightning Data Using WRF-3DVar Combined with the Physical Initialization Method——A Case Study of a Mesoscale Convective System

Radar data, which have incomparably high temporal and spatial resolution, and lightning data, which are great indicators of severe convection, have been used to improve the initial field and increase the accuracies of nowcasting and short-term forecasting. Physical initialization combined with the three-dimensional variational data assimilation method(PI3 DVar_rh) is used in this study to assimilate two kinds of observation data simultaneously, in which radar data are dominant and lightning data are introduced as constraint conditions. In this way, the advantages of dual observations are adopted. To verify the effect of assimilating radar and lightning data using the PI3 DVar_rh method, a severe convective activity that occurred on 5 June 2009 is utilized, and five assimilation experiments are designed based on the Weather Research and Forecasting(WRF) model. The assimilation of radar and lightning data results in moister conditions below cloud top, where severe convection occurs; thus, wet forecasts are generated in this study.The results show that the control experiment has poor prediction accuracy. Radar data assimilation using the PI3 DVar_rh method improves the location prediction of reflectivity and precipitation, especially in the last 3-h prediction, although the reflectivity and precipitation are notably overestimated. The introduction of lightning data effectively thins the radar data, reduces the overestimates in radar data assimilation, and results in better spatial pattern and intensity predictions. The predicted graupel mixing ratio is closer to the distribution of the observed lightning,which can provide more accurate lightning warning information.