National Reference Stations Research Articles

The current situation of Russia’s GNSS continuous operating reference station network and thinking on future development

The GNSS (Global Navigation Satellite Systems) continuous operating reference station network not only provides a reliable technical foundation and data support for achieving high-precision navigation and positioning services, but also can be integrated with other Earth observation systems (such as laser ranging, gravity measurement, etc.) to improve the accuracy and stability of Earth observation data. It is used to establish regional and global coordinate frameworks and provide data to support scientific research such as seismology, geo-tectonics, and oceanography. This article first systematically introduces the construction, development history and current situation of the Russian GNSS continuous operating reference station network, and then carefully analyzes the construction, operation, and application status and existing problems of the Russian reference station network. Finally, after careful consideration, it discusses the problems and challenges faced in the planning of reference station network construction, equipment localization, and national unified reference station network construction, and provides some suggestions and ideas.

Analyses of Vineyard Microclimate in the Eastern Foothills of the Helan Mountains in Ningxia Region, China

Vineyard microclimate is a main determining factor for grape yield and quality. In the Eastern Foothills of the Helan Mountains in the Ningxia region, China, grape is a critical economic crop for wine making. The microclimate of vineyards in 2019 and 2020 was analyzed on the basis of observations from eight vineyards microclimate stations and a national reference station. The vineyard microclimate was compared with the larger-scale local weather conditions, and the vineyard microclimate was compared within and among different climatic zones. In addition, the climate was evaluated at the four study wine grape areas. The results showed that: (1) In the same wine-grape-growing area where the climate was similar, vineyard microclimate was affected by elevation, topography, and soil texture. (2) Excepting average wind velocity, there were no statistically significant (p < 0.05) differences in minimum and maximum air temperatures or relative humidity between the study field microclimate observation stations and the local national reference station. (3) Among the four climate-zone-based wine-grape-growing areas, vineyard microclimate was related to topography, geographical location, and soil type. In particular, the Yinchuan and Qingtongxia areas had an abundant heat resource, and the Hongsipu area had sufficient precipitation and high photosynthetically active radiation (PAR). By contrast, the Shizuishan area had a relatively low-to-moderate amount of heat, precipitation, and radiation resources for grape. (4) According to the climate assessment of agricultural products—wine grape (QX/T 557—2020), the climate was superior in 2019 than in 2020 for wine grapes. In particular, the climate for grape was better in the Yinchuan area than in other study areas. The results of this study are evidence-based and could be used to assist the local wine grape community in making decisions about cultivars, management practices, area expansions, marketing strategies, etc.

Variations of Extreme Temperature Event Indices in Six Temperature Zones in China from 1961 to 2020

In this study, eight extreme temperature event indices were calculated based on daily maximum, minimum, and mean temperature data recorded at 699 National Reference Stations in China during 1961–2020. The yearly change of mean temperature and the magnitude, frequency, and duration of extreme temperature events in six temperature zones were evaluated. All temperature zones had a trend of an increase in mean temperature (rate: 2.1–3.3 °C per 10 years), and the warming was more significant in the warm temperate zone and the Qinghai–Tibet Plateau zone (QPZ). For extreme temperature events, the extreme maximum and minimum temperatures in most temperature zones showed significant trends of increase, and the rates of increase were greater in the northern zones and QPZ. The rate of increase in extreme minimum temperature was substantially (up to three times) higher than the rate of increase in extreme maximum temperature in the same temperature zone; however, the finding was the opposite for the cold temperate zone (CTZ), which is the northernmost region of China. The rate of increase in extreme maximum temperatures was the greatest (0.35 °C per 10 years), whereas the rate of increase in extreme minimum temperatures was the smallest (0.17 °C per 10 years). The number of warm days/nights and the warm spell duration index also showed significant trends of increase that were most obvious in the southern zones and QPZ. In the tropical zone (TZ), which is the southernmost part of mainland China, the number of warm nights was only 15.3 days in 1961–1970, whereas it increased to 61.9 days in 2011–2020 (an increase of 303.9%). The rate of increase in warm nights in TZ (8.8 days per 10 years) was four times that in CTZ (2.2 days per 10 years). The number of cold days/nights and the cold spell duration index showed significant trends of decrease, with the greatest rates of reduction in QPZ and TZ. In evaluating the frequency of extreme temperature events, the amplitude of warming of the night index was found to be greater than that of the day index. In evaluating the duration of extreme temperature events, the variation of the cold index was found to be greater than that of the warm index. The notable asymmetries found in the variations of the minimum/maximum temperatures, day/night indices, and cold/warm spell durations in China are direct manifestations of global warming.

RESEARCH IMPLEMENTATION OF BEIDOU DATA FAST PROCESSING OF LARGE-SCALE GNSS REFERENCE STATION NETWORK

Abstract. GNSS reference station network is the core infrastructure for the establishment ,maintenance, renewal and service of national geodetic reference framework. At present ,nearly 3000 reference stations have been constructed in the national resources system ,of which about 2500 stations have the continuous observation capacity of BDS signal. In the face of daily massive observation data, the traditional sub-network and fully combined baselines can not meet the needs of rapid data processing for the maintenance of geodetic coordinate framework.In this paper, the high-precision and fast processing of BDS observation data of large-scale GNSS reference station network (≥ 300 stations) is realized through modular design, non difference model, parameter management to be estimated and flexible ambiguity processing. Through the whole network calculation of the 7-day BDS observation data of about 500 MGEX stations and national reference stations that selected all around the world from 211 to 217 days in 2017, the positioning results show that the average RMS values of the coordinates in the three directions of station N,E and U are ±2.3mm, ±2.8mm and ±4.6mm respectively. The orbit determination results show that the average accuracy of GPS satellite orbit in three directions is better than ±2cm; BDS MEO / IGSO track accuracy is better than ±20cm and GEO track accuracy is better than ±200cm.

Multi-decadal ocean temperature time-series and climatologies from Australia\u2019s long-term National Reference Stations

Multi-decadal ocean time-series are fundamental baselines for assessing the impacts of environmental change, however, compiling and quality controlling historic data from multiple sources remains challenging. Here we aggregate, document, and release a number of long time-series temperature products and climatologies compiled from data obtained at 4 monitoring sites around Australia where sub-surface ocean temperature has been recorded nominally weekly to monthly since the 1940s/50s. In recent years, the sampling was augmented with data obtained from moored sensors, vertical profiles and satellite-derived data. The temperature data have been quality controlled, and combined using a rigorously tested methodology. We have packaged the multi-decadal, multi-depth, multi-platform temperature time-series at each site and produced a range of daily temperature climatologies from different data combinations and time periods. The 17 data products are provided as CF-compliant NetCDF files and will be updated periodically. The long-term temperature time-series will be useful for studies of ocean temperature variability, trends, anomalies and change. The data collection is supported by Australia’s Integrated Marine Observing System and data are open-access.

ANALYSIS OF POSITIONING DEVIATION BETWEEN BEIDOU AND GPS BASED ON NATIONAL REFERENCE STATIONS IN CHINA

Abstract. In order to probe into the characteristics of positioning deviation between Beidou Navigation Satellite System (Beidou) and global positioning system (GPS), and investigate possible contribution of Beidou data to refinement of global coordinate system, refined calculation is made on observation data of 240 national reference stations that are distributed uniformly across China on the whole in this study. These stations support satellite signals of four global navigation satellite systems, including Beidou, GPS, GLONASS and Galileo, and a 5-year time span from 2016 to 2020 is adopted. In this study, PPP is calculated based on GPS data and Beidou single system data in no-difference resolution network mode, and accurate coordinates of national reference stations in two processing modes are obtained. Analysis of difference between the calculations based on Beidou data and on GPS data shows that the consistency between Beidou and GPS positioning results reaches about 5 mm in the east and in the north, and about 1.3 cm in the height direction.

Application of adjustment with contrainned codition in mixed GNSS, levelling control network and improving accuracy of the Geoid model

One of the important contents to achieve the goal of modernization of the height system is connect the levelling observations between national levelling order I, II to the national GNSS Continuous Operating Reference Stations and the national gravity marks. Today, Vietnamese surveyors commonly use Geoid model 2010 that built based on more than 3000 gravity marks and over 800 GPS-levelling points. The processing combined GNSS-levelling and gravity obervations to improve the Geoid model for archiving accuracy from 4 to 10 centimeters, that can be possible to apply topographic heigh using GNSS accurately instead of traditional levelling is necessary for geomatics and mapping in Vietnam. There are some researchs in the literature aim to improving geoid model. In these research, the interpolation methods are mainly discussed such as collocation, linear function order 1, 2 or spline function. In this paper, the objective is to consider and propose a method of data processing using theothy of adjustment with contrainned codition and analyze the covariance matrix of the input data.

Daily Subsurface Ocean Temperature Climatology Using Multiple Data Sources: New Methodology

The availability and accessibility of oceanographic data is critical to the sustainability of our oceans into the future. Ocean temperature climatology data products utilising long time series provide context to ocean warming and allow the identification of anomalous environmental conditions. Here we describe a new methodology to create a daily subsurface temperature climatology using data from three different sources with varying spatial and temporal coverage. The Port Hacking National Reference Station off South East Australia is the site of bottle data collected typically every 1 to 4 weeks at discrete depths between 1953 and 2010, and since 2009 near-monthly vertical profiling CTD profiles and 5 minute moored data at various depths. Calculating an unbiased climatology using temperature data sets obtained via different methods, with varying resolution and uncertainty, is challenging. To account for days with limited bottle data, and thus limit the bias from more recent higher temporal resolution data, a time-centered moving window of±2 days was used to incorporate data collected on neighbouring days. To account for different data sources measured on the same date, a date-averaging method was used. As moored data between 2009 and 2019 represented 70 % of data for a given day of the year but approximately 1/7 of the 66 year temperature record, a novel data source ratio was implemented to avoid bias towards warmer recent years. Data were organised into their corresponding observed years, and a ratio of 6:1 between bottle and mooring observation years was enforced. To assess the methodology, the steps provided here were tested using synthetically-created temperature data with similar properties to the real observations. The lowest root mean square errors calculated between the known synthetic climatology statistics and the different solution-dependent synthetic climatology statistics confirmed the methodology. The resulting daily temperature climatology shows the seasonal cycle as a function of depth, related to changes in stratification and vertical mixing, and allows for the identification of temperature anomalies. The methodology presented in this paper is readily applicable to other sites across Australia and worldwide where long records exist consisting of multiple data sets with varying sampling characteristics.

Daily Subsurface Ocean Temperature Climatology Using Multiple Data Sources: New Methodology

The availability and accessibility of oceanographic data is critical to the sustainability of our oceans into the future. Ocean temperature climatology data products utilising long time series provide context to ocean warming and allow the identification of anomalous environmental conditions. Here we describe a new methodology to create a daily subsurface temperature climatology using data from three different sources with varying spatial and temporal coverage. The Port Hacking National Reference Station off South East Australia is the site of bottle data collected typically every 1 to 4 weeks at discrete depths between 1953 and 2010, and since 2009 near-monthly vertical profiling CTD profiles and 5 minute moored data at various depths. Calculating an unbiased climatology using temperature data sets obtained via different methods, with varying resolution and uncertainty, is challenging. To account for days with limited bottle data, and thus limit the bias from more recent higher temporal resolution data, a time-centered moving window of±2 days was used to incorporate data collected on neighbouring days. To account for different data sources measured on the same date, a date-averaging method was used. As moored data between 2009 and 2019 represented 70 % of data for a given day of the year but approximately 1/7 of the 66 year temperature record, a novel data source ratio was implemented to avoid bias towards warmer recent years. Data were organised into their corresponding observed years, and a ratio of 6:1 between bottle and mooring observation years was enforced. To assess the methodology, the steps provided here were tested using synthetically-created temperature data with similar properties to the real observations. The lowest root mean square errors calculated between the known synthetic climatology statistics and the different solution-dependent synthetic climatology statistics confirmed the methodology. The resulting daily temperature climatology shows the seasonal cycle as a function of depth, related to changes in stratification and vertical mixing, and allows for the identification of temperature anomalies. The methodology presented in this paper is readily applicable to other sites across Australia and worldwide where long records exist consisting of multiple data sets with varying sampling characteristics.

Oceanographic influence on coastal zooplankton assemblages at three IMOS National Reference Stations in Western Australia

Knowledge about the coastal zooplankton of the south-eastern Indian Ocean is limited, with few studies having compared assemblages across the latitudinal range of the western seaboard of Australia. The dominant oceanographic feature in this region is the Leeuwin Current, which transports warm, lower-salinity, tropical waters southward along the shelf-edge. This study examined data collected by Australia’s Integrated Marine Observing System at three coastal National Reference Stations located at 22°S 114°E, 32°S 115°E and 34°S 122°E. Spatial and temporal patterns in zooplankton abundance, composition and diversity were investigated, and differences in assemblage structure, particularly with respect to copepods, were related to oceanographic conditions. Clear dissimilarities among copepod assemblages were observed, becoming weaker in winter owing to enhanced connectivity of species driven by alongshore and cross-shelf transport in the Leeuwin Current. Both physical and biogeochemical factors were significant in structuring copepod assemblages, with seawater density, incorporating temperature and salinity, exerting the greatest influence. The results suggest that both broad-scale latitudinal gradients and mesoscale events contribute to variation in zooplankton assemblages in these waters. This study provides the first detailed comparison of zooplankton assemblages among the north-west, south-west and southern coastal waters of Western Australia, and enhances understanding of the processes influencing zooplankton distribution and structure.

Australia’s Long-Term Plankton Observations: The Integrated Marine Observing System National Reference Station Network

The Integrated Marine Observing System National Reference Station network provides unprecedented open access to species-level phytoplankton and zooplankton data for researchers, managers and policy makers interested in resource condition, and detecting and understanding the magnitude and time-scales of change in our marine environment. We describe how to access spatial and temporal plankton data collected from the seven reference stations located around the Australian coastline, and a summary of the associated physical and chemical parameters measured that help in the interpretation of plankton data. Details on the rationale for site locations, sampling methodologies and laboratory analysis protocols are provided to assist with use of the data, and design of complimentary investigations. Information on taxonomic entities reported in the plankton database, and changes in taxonomic nomenclature and other issues that may affect data interpretation, are included. Data from more than 1250 plankton samples are freely available via the Australian Ocean Data Network portal and we encourage uptake and use of this continental-scale dataset, giving summaries of data currently available and some practical applications. The full methods manual that includes sampling and analysis protocols for the Integrated Marine Observing System Biogeochemical Operations can be found on-line.

REAL-TIME TROPOSPHERIC PRODUCT ESTABLISHMENT AND ACCURACY ASSESSMENT IN CHINA

Abstract. Tropospheric delay has always been an important issue in Global Navigation Satellite System (GNSS) processing. Empirical tropospheric delay models are difficult to simulate complex and volatile atmospheric environments, resulting in poor accuracy of the empirical model and difficulty in meeting precise positioning demand. In recent years, some scholars proposed to establish real-time tropospheric product by using real-time or near-real-time GNSS observations in a small region, and achieved some good results. This paper uses real-time observing data of 210 Chinese national GNSS reference stations to estimate the tropospheric delay, and establishes ZWD grid model in the country wide. In order to analyze the influence of tropospheric grid product on wide-area real-time PPP, this paper compares the method of taking ZWD grid product as a constraint with the model correction method. The results show that the ZWD grid product estimated based on the national reference stations can improve PPP accuracy and convergence speed. The accuracy in the north (N), east (E) and up (U) direction increase by 31.8 %,15.6 % and 38.3 %, respectively. As with the convergence speed, the accuracy of U direction experiences the most improvement.

Phytoplankton absorption predicts patterns in primary productivity in Australian coastal shelf waters

The phytoplankton absorption coefficient (aPHY) has been suggested as a suitable alternate first order predictor of net primary productivity (NPP). We compiled a dataset of surface bio-optical properties and phytoplankton NPP measurements in coastal waters around Australia to examine the utility of an in-situ absorption model to estimate NPP. The magnitude of surface NPP (0.20–19.3 mmol C m−3 d−1) across sites was largely driven by phytoplankton biomass, with higher rates being attributed to the microplankton (>20 μm) size class. The phytoplankton absorption coefficient aPHY for PAR (photosynthetically active radiation; āPHY)) ranged from 0.003 to 0.073 m-1, influenced by changes in phytoplankton community composition, physiology and environmental conditions. The aPHY coefficient also reflected changes in NPP and the absorption model-derived NPP could explain 73% of the variability in measured surface NPP (n = 41; RMSE = 2.49). The absorption model was applied to two contrasting coastal locations to examine NPP dynamics: a high chlorophyll-high variation (HCHV; Port Hacking National Reference Station) and moderate chlorophyll-low variation (MCLV; Yongala National Reference Station) location in eastern Australia using the GIOP-DC satellite aPHY product. Mean daily NPP rates between 2003 and 2015 were higher at the HCHV site (1.71 ± 0.03 mmol C m−3 d−1) with the annual maximum NPP occurring during the austral winter. In contrast, the MCLV site annual NPP peak occurred during the austral wet season and had lower mean daily NPP (1.43 ± 0.03 mmol C m−3 d−1) across the time-series. An absorption-based model to estimate NPP is a promising approach for exploring the spatio-temporal dynamics in phytoplankton NPP around the Australian continental shelf.

Historical reconstruction of ocean acidification in the Australian region

Abstract. The ocean has become more acidic over the last 200 years in response increasing atmospheric carbon dioxide (CO2) levels. Documenting how the ocean has changed is critical for assessing how these changes impact marine ecosystems and for the management of marine resources. Here we use present-day ocean carbon observations, from shelf and offshore waters around Australia, combined with neural network mapping of CO2, sea surface temperature, and salinity to estimate the current seasonal and regional distributions of carbonate chemistry (pH and aragonite saturation state). The observed changes in atmospheric CO2 and sea surface temperature (SST) and climatological salinity are then used to reconstruct pH and aragonite saturation state changes over the last 140 years (1870–2013). The comparison with data collected at Integrated Marine Observing System National Reference Station sites located on the shelf around Australia shows that both the mean state and seasonality in the present day are well represented, with the exception of sites such as the Great Barrier Reef. Our reconstruction predicts that since 1870 decrease in aragonite saturation state of 0.48 and of 0.09 in pH has occurred in response to increasing oceanic uptake of atmospheric CO2. Large seasonal variability in pH and aragonite saturation state occur in southwestern Australia driven by ocean dynamics (mixing) and in the Tasman Sea by seasonal warming (in the case of the aragonite saturation state). The seasonal and historical changes in aragonite saturation state and pH have different spatial patterns and suggest that the biological responses to ocean acidification are likely to be non-uniform depending on the relative sensitivity of organisms to shifts in pH and saturation state. This new historical reconstruction provides an important link to biological observations that will help to elucidate the consequences of ocean acidification.

Climate variability drives plankton community composition changes: the 2010–2011 El Niño to La Niña transition around Australia

The strong La Nina of 2010-2011 provided an opportunity to investigate the ecological impacts of El Nino-Southern Oscillation on coastal plankton communities using the nine national reference stations around Australia. Based on remote sensing and across the entire Australian region 2011 (La Nina) was only modestly different from 2010 (El Nino) with the average temperature declining 0.2 percent surface chlorophyll a up 3 percent and modelled primary production down 14 percent. Other changes included a poleward shift in Prochlorococcus and Synechococcus. Along the east coast, there was a reduction in salinity, increase in nutrients, Chlorophytes and Prasinophytes (taxa with chlorophyll b, neoxanthin and prasinoxanthin). The southwest region had a rise in the proportion of 19-hexoyloxyfucoxanthin; possibly coccolithophorids in eddies of the Leeuwin Current and along the sub-tropical front. Pennate diatoms increased, Ceratium spp. decreased and Scrippsiella spp. increased in 2011. Zooplankton biomass declined significantly in 2011. There was a reduction in the abundance of Calocalanus pavo and Temora turbinata and increases in Clausocalanus farrani, Oncaea scottodicarloi and Macrosetella gracilis in 2011. The changes in the plankton community during the strong La Nina of 2011 suggest that this climatic oscillation exacerbates the tropicalization of Australia.

IMOS National Reference Stations: a continental-wide physical, chemical and biological coastal observing system.

Sustained observations allow for the tracking of change in oceanography and ecosystems, however, these are rare, particularly for the Southern Hemisphere. To address this in part, the Australian Integrated Marine Observing System (IMOS) implemented a network of nine National Reference Stations (NRS). The network builds on one long-term location, where monthly water sampling has been sustained since the 1940s and two others that commenced in the 1950s. In-situ continuously moored sensors and an enhanced monthly water sampling regime now collect more than 50 data streams. Building on sampling for temperature, salinity and nutrients, the network now observes dissolved oxygen, carbon, turbidity, currents, chlorophyll a and both phytoplankton and zooplankton. Additional parameters for studies of ocean acidification and bio-optics are collected at a sub-set of sites and all data is made freely and publically available. Our preliminary results demonstrate increased utility to observe extreme events, such as marine heat waves and coastal flooding; rare events, such as plankton blooms; and have, for the first time, allowed for consistent continental scale sampling and analysis of coastal zooplankton and phytoplankton communities. Independent water sampling allows for cross validation of the deployed sensors for quality control of data that now continuously tracks daily, seasonal and annual variation. The NRS will provide multi-decadal time series, against which more spatially replicated short-term studies can be referenced, models and remote sensing products validated, and improvements made to our understanding of how large-scale, long-term change and variability in the global ocean are affecting Australia's coastal seas and ecosystems. The NRS network provides an example of how a continental scaled observing systems can be developed to collect observations that integrate across physics, chemistry and biology.

Assessing and evaluating the ocean-colour footprint of a regional observing system

A recurring problem with point based marine observations is how to scale them up to infer local and regional dynamics, this is especially true of biogeochemical (BGC) variables such as chlorophyll-a (Chl-a) and dissolved inorganic nutrients. The recent study by Oke and Sakov (2012) uses a combination of historical satellite imagery, and numerical model output to assess the footprint of physical variables in regional observing system. However, in the absence of long integrations of marine biogeochemical models, there are very few tools to interpret the biological dynamics that may be captured by a regional observing system. In this study, a generic approach to assess the biological footprint of regional observing systems is developed. We used the recently reprocessed gridded chlorophyll-a product (NASA OC3M algorithm) to estimate the spatial footprint of the biological observations of the Australian Integrated Marine Observing System (IMOS) National Reference Station (NRS) network at intra-weekly, intra-monthly and intra-seasonal timescales. From this analysis, it is clear that the NRSs are only able to characterize variability at locations close (typically within 9–50km) to the NRS sites at weekly timescales. However, at monthly and seasonal timescales, the NRS footprint is large enough to infer shelf and regional scale dynamics that are representative of substantial portions of the Australian shelf. This is a generic method that can be incorporated into the design and evaluation of regional observing systems where gridded ocean colour products are available.

Quality Control (QC) procedures for Australia’s National Reference Station’s sensor data—Comparing semi-autonomous systems to an expert oceanographer

The National Reference Station (NRS) network, part of Australia’s Integrated Marine Observing System (IMOS), is designed to provide the baseline multi-decadal time series required to understand how large-scale, long-term change and variability in the global ocean are affecting Australia’s coastal ocean ecosystems. High temporal resolution observations of oceanographic variables are taken continuously across the network’s nine moored stations using a Water Quality Monitor (WQM) multi-sensor. The data collected are made freely available and thus need to be assessed to ensure their consistency and fitness-for-use prior to release. Here, we describe a hybrid quality control system comprising a series of tests to provide QC flags for these data and an experimental ‘fuzzy logic’ approach to assessing data. This approach extends the qualitative pass/fail approach of the QC flags to a quantitative system that provides estimates of uncertainty around each data point. We compared the results obtained from running these two assessment schemes on a common dataset to those produced by an independent manual QC undertaken by an expert oceanographer. The qualitative flag and quantitative fuzzy logic QC assessments were shown to be highly correlated and capable of flagging samples that were clearly erroneous. In general, however, the quality assessments of the two QC schemes did not accurately match those of the oceanographer, with the semi-automated QC schemes being far more conservative in flagging samples as ‘bad’. The conservative nature of the semi-automated systems does, however, provide a solution for QC with a known risk. Our software systems should thus be seen as robust low-pass filters of the data with subsequent expert review of data flagged as ‘bad’ to be recommended.

Assessing the footprint of a regional ocean observing system

We define the footprint of an ocean observation as the region that is well correlated to the observed variable at zero time-lag. The footprint of observations from an observation array provides an indication of the region that is effectively monitored by that array. This study examines the footprint of moorings that underpin the Australian Integrated Marine Observing System (IMOS). Based on sea-surface height, temperature, and velocity from a 17-year model run, we quantify the footprint of existing moorings to identify the extent to which the shelf circulation is likely to be represented by those moorings. We find that in combination, the nine long-term National Reference Stations (NRSs) effectively monitor, with a correlation of >0.8, the interannual (intraseasonal) variability of the shelf circulation in about 80% (30%) of the region around Australia. The 28 additional IMOS moorings expand the combined footprint for intraseasonal variability to cover up to 70%. We identify several gaps in the observing system that could be filled by additional observations, including the regions off the east coast, the central Great Barrier Reef, the Great Australian Bight, parts of the north–west shelf, and the Gulf of Carpentaria.

Urban heat island effect on annual mean temperature during the last 50 years in China

Based on China’s fifth population survey (2000) data and homogenized annual mean surface air temperature data, the urban heat island (UHI) effect on the warming during the last 50 years in China was analyzed in this study. In most cities with population over 104, where there are national reference stations and principal stations, most of the temperature series are inevitably affected by the UHI effect. To detect the UHI effect, the annual mean surface air temperature (SAT) time series were firstly classified into 5 subregions by using Rotated Principal Components Analysis (RPCA) according to its high and low frequency climatic change features. Then the average UHI effect on each subregion’s regional annual mean STA was studied. Results indicate that the UHI effect on the annual mean temperatures includes three aspects: increase of the average values, decrease of variances and change of the climatic trends. The effect on the climatic trends is different from region to region. In the Yangtze River Valley and South China, the UHI effect enhances the warming trends by about 0.011 °C/decade. In the other areas, such as Northeast, North-China, and Northwest, UHI has little impact on the warming trends of the regional annual temperature; while in the Southwest of China, introducing UHI stations slows down the warming trend by −0.006 °C/decade. But no matter what subregion it is, the total warming/cooling of these effects is much smaller than the background change in regional temperature. The average UHI effect for the entire country, during the last 50 years is less than 0.06 °C, which agrees well with the IPCC (2001). This suggests that we cannot conclude that urbanization during the last 50 years has had much obvious effect on the observed warming in China.