Observing System Requirements Research Articles

Rancang Bangun Sistem Informasi Komunitas Burung Murai Batu Pati Berbasis Web

The number of stone magpie lovers and breeders with many who capture the beauty of their birds through social media uploads. Because magpies have beautiful patterns and chirps, many people have become lovers and breeders. Currently magpie bird lovers follow the competition getting information from whatsapp messages. This becomes an obstacle, when there are communities that do not have whatsapp or miss information. Magpie bird lovers and breeders still need a system to interact, discuss, and find information about magpie birds in one place. This research has the benefit of providing a place for magpie bird lovers and breeders to interact easily so that a website-based Pati magpie bird community information system is developed. With a website-based system, magpie bird lovers are more updated in getting information. The data collection methods used in this research are interviews, observations and documentation. Interviews were conducted by interviewing stone magpie bird lovers followed by observing system requirements. This system was created using the codeigniter framework and using the research development method, namely waterfall.

Improvement of GOCI-II Water Vapor Absorption Correction through Fusion with GK-2A/AMI Data

In remote sensing of the ocean color, in particular, in coarse-resolution global model simulations, atmospheric trace gases including water vapor are generally treated as auxiliary data, which create uncertainties in atmospheric correction. The second Korean geostationary satellite mission, Geo-Kompsat 2 (GK-2), is unique in combining visible and infrared observations from the second geostationary ocean color imager (GOCI-II) and the advanced meteorological imager (AMI) over Asia and the Pacific Ocean. In this study, we demonstrate that AMI total precipitable water (TPW) data to allow realistic water vapor absorption correction of GOCI-II color retrievals for the ocean. We assessed the uncertainties of two candidate TPW products for GOCI-II atmospheric correction using atmospheric sounding data, and then analyzed the sensitivity of four ocean-color products (remote sensing reflectance [Rrs], chlorophyll-a concentration [CHL], colored dissolved organic matter [CDOM], and total suspended sediment [TSS]) for GOCI-II water vapor transmittance correction using AMI and global model data. Differences between the TPW sources increased the mean absolute percentage error (MAPE) of Rrs from 2.97% to 6.43% in the blue to green bands, higher than the global climate observing system requirements (<5%) at 412 nm. By contrast, MAPE values of 3.53%, 6.18%, and 7.71% were increased to 6.63%, 13.53%, and 16.14% at high sun and sensor zenith angles for CHL, CDOM, and TSS, respectively. Uncertainty analysis provided similar results, indicating that AMI TPW produced approximately 3-fold lower error rates in ocean-color products than obtained using TPW values from the National Centers for Environmental Prediction. These results imply that AMI TPW can improve the accuracy and ability of GOCI-II ocean-color products to capture diurnal variability.

The ocean pole tide loading and its effect on GPS position time-series

SUMMARY The changes in the centrifugal force induced by polar motion perturb the ocean, causing an ocean pole tide. The induced displacements due to the ocean pole tide, namely ocean pole tide loading (OPTL), previously ignored, raises the concerns in the GPS data processing with the increasing accuracy of Global Position System (GPS) technique. Though the amplitude of this effect is small, it is worth to demonstrate the magnitude and its impact on GPS solutions of the processing choices for correcting it from observations or onto estimated coordinates. For OPTL modelling, subdaily polar motion can introduce annual variations in OPTL with the small magnitudes in micrometres. The new secular pole model can cause OPTL vertical velocity difference up to 0.03 mm yr−1 compared with the mean pole model of International Earth Rotation and Reference System Service Conventions (2010). The OPTL deformation is dominated by the annual (∼365.25 d) and Chandler (∼433 d) periods, and the largest peak-to-peak variations can reach 0.70, 0.84 and 2.38 mm for East, North and Up components, respectively. We then investigate the effects of OPTL correction on GPS daily positions of 133 stations from 2014 to 2018. The root mean square of OPTL induced GPS daily displacements can reach submillimetre level. In most cases, a posteriori OPTL correction with daily averaged values applied onto the coordinates is acceptable considering the small deviation between the solution removing OPTL from coordinates and the solution correcting OPTL from observations. However, this does not hold when GPS coordinates have been aligned to a secular reference frame, as the annual/Chandler variations of OPTL would be biased. When reference frame alignment is required, either OPTL correction at observation level or a posteriori OPTL correction before reference frame alignment is recommended. Furthermore, we have demonstrated that the effects of OPTL on the annual variations of GPS position time-series can reach as much as 0.4 mm in the verticals. It has limited effect on the linear velocity and reduction of the residuals scatter (annual variations excluded), within Global Geodetic Observing System requirements for the future terrestrial reference frame at millimetre level.

What are the greenhouse gas observing system requirements for reducing fundamental biogeochemical process uncertainty? Amazon wetland CH<sub>4</sub> emissions as a case study

Abstract. Understanding the processes controlling terrestrial carbon fluxes is one of the grand challenges of climate science. Carbon cycle process controls are readily studied at local scales, but integrating local knowledge across extremely heterogeneous biota, landforms and climate space has proven to be extraordinarily challenging. Consequently, top-down or integral flux constraints at process-relevant scales are essential to reducing process uncertainty. Future satellite-based estimates of greenhouse gas fluxes – such as CO2 and CH4 – could potentially provide the constraints needed to resolve biogeochemical process controls at the required scales. Our analysis is focused on Amazon wetland CH4 emissions, which amount to a scientifically crucial and methodologically challenging case study. We quantitatively derive the observing system (OS) requirements for testing wetland CH4 emission hypotheses at a process-relevant scale. To distinguish between hypothesized hydrological and carbon controls on Amazon wetland CH4 production, a satellite mission will need to resolve monthly CH4 fluxes at a ∼ 333 km resolution and with a ≤ 10 mg CH4 m−2 day−1 flux precision. We simulate a range of low-earth orbit (LEO) and geostationary orbit (GEO) CH4 OS configurations to evaluate the ability of these approaches to meet the CH4 flux requirements. Conventional LEO and GEO missions resolve monthly ∼ 333 km Amazon wetland fluxes at a 17.0 and 2.7 mg CH4 m−2 day−1 median uncertainty level. Improving LEO CH4 measurement precision by 2 would only reduce the median CH4 flux uncertainty to 11.9 mg CH4 m−2 day−1. A GEO mission with targeted observing capability could resolve fluxes at a 2.0–2.4 mg CH4 m−2 day−1 median precision by increasing the observation density in high cloud-cover regions at the expense of other parts of the domain. We find that residual CH4 concentration biases can potentially reduce the ∼ 5-fold flux CH4 precision advantage of a GEO mission to a ∼ 2-fold advantage (relative to a LEO mission). For residual CH4 bias correlation lengths of 100 km, the GEO can nonetheless meet the ≤ 10 mg CH4 m−2 day−1 requirements for systematic biases ≤ 10 ppb. Our study demonstrates that process-driven greenhouse gas OS simulations can enhance conventional uncertainty reduction assessments by quantifying the OS characteristics required for testing biogeochemical process hypotheses.

How Much of Monthly Subsurface Temperature Variability in the Equatorial Pacific Can Be Recovered by the Specification of Sea Surface Temperatures?

Abstract The focus of the analysis is to investigate the question to what extent the specification of sea surface temperature (SST) in coupled model integration can impart realistic evolution of subsurface ocean temperature in the equatorial tropical Pacific. In the context of El Niño–Southern Oscillation (ENSO) prediction, the analysis is of importance from two aspects: such a system can be considered as a simple coupled ocean data assimilation system that can provide ocean initial conditions; and what additional components of the ocean observing system may be crucial for skillful ENSO prediction. The results indicate that coupled model integration where SST is continuously nudged toward the observed state can generate a realistic evolution of subsurface ocean temperature. The evolution of slow variability related to ENSO, in particular, has a good resemblance against the observational counterpart. The realism of subsurface ocean temperature variability is highest near the date line and least in the far eastern Pacific where the thermocline is shallowest. The results are also discussed in the context of ocean observing system requirements for ENSO prediction.

Integrated Ocean Observing System in Support of Forecasting Harmful Algal Blooms

AbstractHarmful algal bloom (HAB) events threaten human health, living marine resources, and ecosystem health. Their occurrence has increased in frequency, duration, and severity over the last several decades. Preventing, controlling, or mitigating the impacts of HABs requires the development of permanent, operational ocean observing systems that continuously provide the data and information necessary for rapid detection and timely forecasts of changes in ecosystem states. Key elements of such observing systems are observations and modeling that must be efficiently linked via data management and communication networks. Building the observing system begins by integrating existing assets, is followed by incorporation of new technologies and knowledge, and is guided by the data and information needs of decision makers. User needs are particularly important for development of operational forecast models and new sensors for measuring required biological (e.g., HAB species abundance) and chemical (e.g., concentrations of HAB toxins) variables in near real time. This article describes operational observing system requirements for a HAB forecasting system and current efforts by Regional Associations to develop these observing systems for targeted species in their respective regions.

Climate Change, Sustainable Development and Coastal Ocean Information Needs

Local expressions of climate change are threatening the capacity of coastal ecosystems to support goods and services valued by society on a global scale. As articulated in many international and national ocean policies, conventions and agreements, there is widespread agreement that adaptive, ecosystem-based approaches are needed to manage climate risks and to adapt to the impacts of climate change on our environment. Design and implementation of such approaches requires routine and continuous provision of data and information that enable regular assessments of the states of marine and estuarine ecosystems, changes in states and likely future states in terms of their capacity to support goods and services. The provision of these data and information is a major goal of the climate and coastal modules of the Global Ocean Observing System (GOOS), the oceans and coastal component of the Global Earth Observing System, which is coming into being through an international effort led by the World Meteorological Organization (WMO) and the Intergovernmental Oceanographic Commission (IOC) to integrate, improve and build on existing monitoring and modelling capabilities.The objective is to establish sustained, integrated and interoperable approaches that efficiently link observations and models through data management and communications on national, regional and global scales. Initial requirements for the climate module have been completed and global implementation has begun. However, implementation of coastal GOOS has been slow and uneven geographically, especially in the coastal zones of developing countries and emerging economies. Challenges that must be addressed to move this process along more rapidly and effectively include (a) capacity building; (b) reaching international agreements that enable timely exchanges of data on the states and changing states of coastal ecosystems regionally and globally; (c) achieving international consensus on priorities for phased implementation of coastal GOOS strategic plans; (d) establishing mechanisms to transition advances in science and technology into operational modes as needed; (e) effecting regional and global coordination and collaboration among coastal nations and existing regional bodies with related goals and data requirements; and (f) coordinating the development of the climate and coastal modules of GOOS. Issues associated with these challenges are discussed and the current effort of the GOOS Scientific Steering Committee to document observing system requirements for the coastal ocean is described.

Measurement Requirements for Climate Monitoring of Upper-Air Temperature Derived from Reanalysis Data

Abstract Using a reanalysis of the climate of the past half century as a model of temperature variations over the next half century, tests of various data collection protocols are made to develop recommendations for observing system requirements for monitoring upper-air temperature. The analysis focuses on accurately estimating monthly climatic data (specifically, monthly average temperature and its standard deviation) and multidecadal trends in monthly temperatures at specified locations, from the surface to 30 hPa. It does not address upper-air network size or station location issues. The effects of reducing the precision of temperature data, incomplete sampling of the diurnal cycle, incomplete sampling of the days of the month, imperfect long-term stability of the observations, and changes in observation schedule are assessed. To ensure accurate monthly climate statistics, observations with at least 0.5-K precision, made at least twice daily, at least once every two or three days are sufficient. Using these same criteria, and maintaining long-term measurement stability to within 0.25 (0.1) K, for periods of 20 to 50 yr, errors in trend estimates can be avoided in at least 90% (95%) of cases. In practical terms, this requires no more than one intervention (e.g., instrument change) over the period of record, and its effect must be to change the measurement bias by no more than 0.25 (0.1) K. The effect of the first intervention dominates the effects of subsequent, uncorrelated interventions. Changes in observation schedule also affect trend estimates. Reducing the number of observations per day, or changing the timing of a single observation per day, has a greater potential to produce errors in trends than reducing the number of days per month on which observations are made. These findings depend on the validity of using reanalysis data to approximate the statistical nature of future climate variations, and on the statistical tests employed. However, the results are based on conservative assumptions, so that adopting observing system requirements based on this analysis should result in a data archive that will meet climate monitoring needs over the next 50 yr.

The Sydney 2000 Olympic Games Forecast Demonstration Project: Forecasting, Observing Network Infrastructure, and Data Processing Issues

Abstract The Sydney 2000 Olympic Games World Weather Research Programme Forecast Demonstration Project (WWRP FDP) aimed to demonstrate the utility and impact of modern nowcast systems. The project focused on the use of radar processing systems and products for nowcasting, including severe weather. The forecast problems facing the Australian Bureau of Meteorology (BoM) on these short timescales during the FDP are briefly described. The observing system is then discussed and enhancements to the network that supported the Olympic Games forecast requirements and the WWRP FDP project are outlined. In particular, issues related to radar calibration and quality control are discussed in some detail. The paper concludes with a brief discussion on the observing system requirements to meet such modern nowcast systems, areas of further development, and impacts that the FDP had on BoM nowcasting systems. The need for end-to-end design of systems from data gathering, to analysis and product generation is emphasized.