Use Of Satellite Observations Research Articles

Preliminary Results of the JRA-55C, an Atmospheric Reanalysis Assimilating Conventional Observations Only

As a subset of the Japanese 55-year Reanalysis (JRA-55) project, the Meteorological Research Institute of the Japan Meteorological Agency is conducting a global atmospheric reanalysis that assimilates only conventional surface and upper air observations, with no use of satellite observations, using the same data assimilation system as the JRA-55. The project, named the JRA-55 Conventional (JRA-55C), aims to produce a more homogeneous dataset over a long period, unaffected by changes in historical satellite observing systems. The dataset is intended to be suitable for studies of climate change or multi-decadal variability. The climatological properties deduced from the early results of the JRA-55C are similar to those of the JRA-55 in the troposphere and lower stratosphere, except for high southern latitudes. On the basis of forecast skill, the quality of the JRA-55C is inferior to that of the JRA-55, but the JRA-55C has better temporal homogeneity than the JRA-55. The skill of the latter changes during the JRA-55 period. We have completed 85% of the entire JRA-55C calculation as of February 2014. We expect that the JRA-55C will contribute to a much better understanding of the impact of changes in observing systems on climate trends and variability estimated from the JRA-55.

The use of aircraft for meteorological research in the United Kingdom

ABSTRACTAtmospheric observations from aircraft have played an important role in meteorological research for many years; this paper presents an overview of meteorological research done with research aircraft in the United Kingdom. Key developments from throughout the history of meteorological research flying in the United Kingdom are presented, along with highlights of UK atmospheric research flying done in the last decade using the Facility for Airborne Atmospheric Measurements (FAAM) BAe‐146 aircraft. The work presented includes research into thermodynamics, cloud processes, atmospheric aerosol, radiative transfer and atmospheric chemistry. Research aircraft provide a unique platform for the observation of atmospheric processes, allowing targeted measurement of specific parameters at a range of altitudes throughout the atmosphere. These measurements have improved greatly the understanding of the Earth's atmosphere, and the impact of these measurements has been seen through improvements in the representation of physical processes within numerical weather prediction (NWP) and climate models. Research aircraft have also been used extensively for the calibration and validation of remote sensing measurements, providing a unique test‐bed for satellite observations. This research has led to improved use of satellite observations that have enhanced greatly how the atmosphere is viewed. Many developments in atmospheric research would not have been possible without the use of aircraft measurements, and these measurements will continue to play a key role in future developments of meteorological observation and prediction, as the complexity and resolution of weather and climate models increases.

Аналіз невизначеностей в задачах оцінки кліматичних змін на регіональному рівні за даними супутникових спостережень парникових газів

Аналіз невизначеностей в задачах оцінки кліматичних змін на регіональному рівні за даними супутникових спостережень парникових газів

Wind over Terra Nova Bay (Antarctica) during a polynya event: Eta model simulations and satellite microwave observations

A study of Terra Nova Bay (TNB) winter polynya, based on the combined use of satellite observations and limited area model simulations, is presented. First, data from passive microwave observations are used to investigate the polynya area daily variability. Second, the Eta model is run to simulate the low-level wind over a defined TNB polynya, located in according to the satellite images, during the period 15-17 September 2003. A preliminary set up of initial and boundary conditions is used. The Eta model is initialized with the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses, with the National Centers for Environmental Prediction (NCEP) of the U.S. National Weather Service data and with information from satellite images providing a realistic extension of the polynya under study. The Eta model simulates a katabatic wind system which develops qualitatively in agreement with the polynya extent, as shown in the satellite images during the same period. The results demonstrate the strong effect of the polynya when included in the initialization of model integrations: the low-level wind is intensified by the presence of the warm area corresponding to the polynya, it is spatially variable and significantly different from one simulated along the coast of the Nansen Ice Sheet. The results of numerical simulations with different surface temperatures in the polynya area are shown as well, thus an assessment of the range of variability of the wind intensity in relation to the polynya surface temperature is provided.

Enhanced radiance bias correction in the National Centers for Environmental Prediction's Gridpoint Statistical Interpolation data assimilation system

AbstractRadiance bias correction is an important and necessary step in the proper use of satellite observations in a data assimilation system. The original radiance bias‐correction scheme used in the Gridpoint Statistical Interpolation (GSI) data assimilation system consists of two components: a variational air‐mass dependent component and a scan‐angle component. The air‐mass component is updated within the GSI, while the scan‐angle component is updated outside the GSI.This study examines and enhances several aspects of the radiance bias‐correction problem. First, a modified pre‐conditioning is applied to the bias‐correction coefficients and the analysis variables to speed up convergence of the minimization process. A new procedure for applying the modified pre‐conditioning in the GSI is utilized. Second, capabilities for detecting any new/missing/recovering radiance data and initializing the bias correction for new radiance data are implemented. A new scheme is proposed and employed to adjust the background‐error variances for the bias‐correction coefficients automatically, using an approximation of the analysis‐error variances from the previous cycle, and to remove the pre‐specified predictor scaling parameters. Finally, the capability to perform bias correction for passive channels within the GSI is developed with a new approach.The two‐step bias‐correction procedure originally used is replaced with a one‐step variational bias‐correction scheme within the GSI. Experiment results with the GSI‐based hybrid ensemble‐variational system show that using the modified pre‐conditioning leads to a better convergence rate. Moreover, with the one‐step scheme, the anomaly correlation of geopotential height at 500 mb is neutral in the Northern Hemisphere but improved in the Southern Hemisphere. The root‐mean‐square (RMS) error of wind is comparable to that of the two‐step scheme and the biases of the global temperature 24 h and 48 h forecasts fitted to the rawinsonde are reduced.

Diagnosing evaporative fraction over land from boundary‐layer clouds

AbstractThe potential use of continental fair‐weather shallow cumuli as a way to retrieve the daily surface evaporative fraction over land is evaluated in convective conditions. The proposed method utilizes the fact that both the timing of cloud occurrence and the cloud‐base height at the time of occurrence provide strong constraints on the surface energy balance and evaporative fraction. The retrieval is especially reliable in the presence of relatively stable and humid‐free troposphere profiles. The advantage of the method is that it provides a more direct estimate of the surface evaporative fraction than indirect estimation based on inversion of a highly parameterized land‐surface model. In addition, the evaporative fraction is obtained at a scale of a few kilometers, which is more pertinent for weather and climate studies. The retrieval strategy is tested and validated for three contrasting climates: the U.S. southern Great Plains, West Africa, and the Netherlands. We suggest that the use of satellite observations of shallow cumuli can help constrain the retrieval of the surface evaporative fraction within a data assimilation scheme/reanalysis.

Aerosol effect on the warm rain formation process: Satellite observations and modeling

This study demonstrates how aerosols influence the liquid precipitation formation process. This demonstration is provided by the combined use of satellite observations and global high‐resolution model simulations. Methodologies developed to examine the warm cloud microphysical processes are applied to both multi‐sensor satellite observations and aerosol‐coupled global cloud‐resolving model (GCRM) results to illustrate how the warm rain formation process is modulated under different aerosol conditions. The observational analysis exhibits process‐scale signatures of rain suppression due to increased aerosols, providing observational evidence of the aerosol influence on precipitation. By contrast, the corresponding statistics obtained from the model show a much faster rain formation even for polluted aerosol conditions and much weaker reduction of precipitation in response to aerosol increase. It is then shown that this reduced sensitivity points to a fundamental model bias in the warm rain formation process that in turn biases the influence of aerosol on precipitation. A method of improving the model bias is introduced in the context of a simplified single‐column model (SCM) that represents the cloud‐to‐rain water conversion process in a manner similar to the original GCRM. Sensitivity experiments performed by modifying the model assumptions in the SCM and their comparisons to satellite statistics both suggest that the auto‐conversion scheme has a critical role in determining the precipitation response to aerosol perturbations and also provide a novel way of constraining key parameters in the auto‐conversion schemes of global models.

Efficiency based wheat yield prediction in a semi-arid climate using surface energy budgeting with satellite observations

Accurate pre-harvest assessment of a staple food crop is an integral part of policy formulation in relation to food security issues. Here, two different approaches were attempted to estimate wheat yield using time series multi-year satellite (MODIS Aqua) optical-thermal data from a single earth observation (EO) mission. Surface energy budgeting was used to estimate evapotranspiration in terms of latent heat fluxes from net available energy and evaporative fraction to predict wheat yield over four agro-climate zones in semi-arid climate of Gujarat, India. Satellite based estimates of latent heat fluxes were found to show substantially less error with respect to the area-averaged heat flux measurements from LAS (large aperture scintillometer) as compared to measurements from BREB (Bowen Ratio Energy Balance) alone. The deviations in satellite based zonal CWU were found to have a strong correlation ( r = 0.71) with the deviations from zonal wheat yield. Among both the approaches, the radiation use efficiency ( RUE) based approach produced better accuracy in the predicted yield with lower root mean square error (RMSE) of 390 kg ha −1 (14.8% of reported mean) and higher correlation coefficient ( r = 0.92) than the water use efficiency ( WUE) based approach (RMSE 573 kg ha −1, 21.8% of reported mean; r = 0.80). Uncertainties in the satellite based core inputs resulted into a net 10-12% error in predicted yield in case of RUE approach. Our demonstrative case studies recommend that the coupled use of satellite observations from multiple EO missions and radiative transfer simulation would be effective to make efficiency based approaches operationally viable for regional wheat yield forecasting in near real time.

From Observations to Forecasts – Part 8: The use of satellite observations in numerical weather prediction

From Observations to Forecasts – Part 8: The use of satellite observations in numerical weather prediction

Progress in the determination of the sea spray source function using satellite data

Sea spray aerosol influences climate considerably through both direct and indirect aerosol effects. Climate models contain a sea spray source function, i.e. the emission rate of sea spray aerosol droplets per unit area of the sea surface, currently parameterised in terms of wind speed and sea surface temperature (SST). The uncertainty between different formulations of the sea spray source function, and thus associated with the calculated emission fluxes for sea spray aerosol, is more than a factor of 2. In addition, the fraction of organic material in sub-micrometer sea spray droplets is highly uncertain. It is expected that improved estimates can be obtained by inclusion of factors, such as wave conditions, whitecap fraction, improved SST, salinity, and chlorophyll concentration. We aim to incorporate these factors in a new sea spray emission model constrained by the use of satellite observations. Here, we present a methodology for estimating the global primary marine sub-micron organic matter emission. As a first estimate we found an annual global emission of about 20 TgC.

Spatial observation of the ozone layer

This article provides an overview of the various satellite instruments, which have been used to observe stratospheric ozone and other chemical compounds playing a key role in stratospheric chemistry. It describes the various instruments that have been launched since the late 1970s for the measurement of total ozone column and ozone vertical profile, as well as the major satellite missions designed for the study of stratospheric chemistry. Since the discovery of the ozone hole in the early 1980s, spatial ozone measurements have been widely used to evaluate and quantify the spatial extension of polar ozone depletion and global ozone decreasing trends as a function of latitude and height. Validation and evaluation of satellite ozone data have been the subject of intense scientific activity, which was reported in the various ozone assessments of the state of the ozone layer published after the signature of the Montreal protocol. Major results, based on satellite observations for the study of ozone depletion at the global scale and chemical polar ozone loss, are provided. The use of satellite observations for the validation of chemistry climate models that simulate the recovery of the ozone layer and in data assimilation is also described.

Particulate Matter at Surface: Northern Italy Monitoring Based on Satellite Remote Sensing, Meteorological Fields, and in-situ Samplings

Growing attention has been paid over recent years to the possibility of monitoring surface particulate matter (PM) concentrations through the use of satellite observations. Satellite remote sensing of both aerosol and trace gas constituents can be usefully employed in air quality monitoring (AQ). The MODIS (Terra-Aqua/NASA platforms) aerosol optical properties were used here in a semi-empirical approach to estimate PM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2.5</sub> content at ground level. PM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2.5</sub> samplings were employed to convert aerosol optical depth AOD into PM estimates, considering meteorological fields simulated by MM5. Thus, daily maps of satellite-based PM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2.5</sub> concentrations over Northern Italy were derived. Comparison with daily PM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2.5</sub> , sampled on the ground during the QUITSAT project over six validation sites of the Po valley, showed good agreement (R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ¿ 0.68 and R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ¿ 0.59 for MODIS/Terra and MODIS/Aqua, respectively), with the satellite-based concentrations tending to underestimate the values by at most ~20%. Monthly averaged values were also compared providing good agreement, with R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ¿ 0.7 for each platform.

Remote Sensing of Particulate Pollution from Space: Have We Reached the Promised Land?

The Critical Review of Hoff and Christopher, along with the discussants, provides an important perspective on the interface between satellite measurement science and air quality observations. A top-down picture of the usefulness of satellite observations in terms of air quality regulatory and technical support requirements can be summarized. The air quality requirements are (1) determination of compliance with the ambient air quality standards, (2) inference of human and ecosystem exposure, (3) identification of intra- and intercontinental events relevant to EE, (4) establishment of trends in ambient concentrations relevant to accountability, (5) regulatory and forecast model applications, and (6) extension of fundamental knowledge relevant to air quality. Each of these topics is important to air quality management, and each has detailed technical issues associated with spatial and temporal resolution, accuracy, and precision, etc. In any case, one can summarize the broad capabilities of measurement systems to address these requirements as listed in Table 1. From this rather superficial summary table, investigators should be encouraged to forward increased interaction between the various measurement communities and to facilitate the utility of a comprehensive portfolio of measurements and adjunct analyses for improved air quality applications. The Critical Review has done much to educate air quality scientists on the possibilities for using satellite remote sensing for various purposes. However, space scientists also need a better education on air quality science. Recently published reviews on PM air quality measurements are available that complement the Hoff-Christopher paper on this topic. The need for greater collaboration of air quality and space scientists is evident in an article published in the July issue of the journal. Al-Hamdan et al. provide an interesting and useful analysis of relationships between surface air quality and space-based satellite AOD to estimate human exposure. They obtain mostly urban PM data from EPA's Air Quality System (AQS), but they neglect the potentially more useful PM2.5 and chemical speciation data from the nonurban Interagency Monitoring of Protected Visual Environments (IMPROVE) and the Southeastern Aerosol Research and Characterization (SEARCH) networks. They correlate PM2.5 mass with optical depth, although visibility assessments show that light extinction is better represented by a weighted sum of PM2.5 sulfate, nitrate, organic carbon, elemental carbon, and soil dust. Their comparison of hourly measurements with filter measurements does not specify the source of the hourly values as TEOM or BAM. Spatial outliers for ground-level measurements are removed to improve the correlation of PM2.5 with AOD, although these "outliers" are probably real values that relate to human exposure or a nearby source effect. The point here is not to overly criticize a good publication that will be highly cited. The intent is to demonstrate the value of air quality and space scientists working together more closely on this topic. This is something the review authors alluded to in their review, but if, as they concluded, the "promised land" has not been reached, then perhaps it is an appropriate time for the atmospheric community to ask, "Can near-term satellite observations play a role in characterizing broad-based (outdoor) exposure to pollutants and consequently influence public health improvement?" and, if so, then, "What comprehensive, integrated system is needed if satellite observations are to be used together with ground-based observations and modeling to continue improving air quality management options?"

Assessing the value of information for water quality management in the North Sea

Global Earth Observation (GEO) is one of the most important sources of information for environmental resource management and disaster prevention. With budgets for GEO increasingly under pressure, it is becoming important to be able to quantify the returns to informational investments. For this, a clear analytical framework is lacking. By combining Bayesian decision theory with an empirical, stakeholder-oriented approach, this paper attempts to develop such a framework. The analysis focuses on the use of satellite observations for Dutch water quality management in the North Sea. Dutch water quality management currently relies on information from ‘ in situ’ measurements but is considering extending and deepening its information base with satellite observations. To estimate returns to additional investments in satellite observation, we analyze the added value of an extended monitoring system for the management of eutrophication, potentially harmful algal blooms and suspended sediment and turbidity in the North Sea. First, we develop a model to make the potential contribution of information to welfare explicit. Second, we use this model to develop a questionnaire and interpret the results. The results indicate that the expected welfare impact of investing in satellite observation is positive, but that outcomes strongly depend on the accuracy of the information system and the range of informational benefits perceived.

Mapping sediment-laden sea ice in the Arctic using AVHRR remote-sensing data: Atmospheric correction and determination of reflectances as a function of ice type and sediment load

Exploiting the fact that the spectral characteristics of light backscattered from sediment-laden ice differ substantially from those of clean ice and that sediment tends to accumulate at the ice surface during the first melt season, remote-sensing techniques provide a valuable tool for mapping the extent of particle-laden ice in the Arctic basin and assessing its particulate loading. This study considers two fundamental problems that still need to be addressed in order to make full use of satellite observations for this type of assessment: (i) the effects of the atmosphere on surface reflectances derived from radiances measured by the satellite sensor need to be quantified and ultimately corrected for, and (ii) the spectral reflectance of the ice surface as a function of particle loading and sub-pixel distribution needs to be determined in order to derive quantitative estimates from the at-sensor satellite signal. Here, spectral albedos have been computed for different ice surfaces of variable sediment load with a radiative transfer model for sea ice coupled with an optical model for particulates included in sea ice. In a second step, the role of the atmosphere in modulating the surface reflectance signal is assessed with the aid of an atmospheric radiative transfer model applied to a “standard” Arctic atmosphere and surface boundary conditions as prescribed by the sea ice radiative transfer model. A series of sensitivity studies helps assess differences between top-of-the-atmosphere and true surface reflectance and has been utilized to derive a look-up table for atmospheric correction of Advanced Very High Resolution Radiometer (AVHRR) data over sediment-laden sea ice surfaces. In particular, the effects of solar elevation, viewing geometry, and atmospheric properties are considered. The atmospheric corrections are necessary for certain geometries and surface types. Large discrepancies between raw and corrected data are particularly evident in the derived coverage of clean ice and ice with small sediment loading.

Toward a new generation of satellite surface products?

Despite the abundance and variety of remote sensing measurements, land surface characterization from satellite observations is still very challenging. The links between the three sources of surface information, namely the satellite observations, the in situ measurements, and the land surface model outputs, are complex. Innovative techniques have to be developed to merge these information sources and optimize the use of satellite measurements for better surface products and more predictability. Concepts such as multi‐instrument/multiparameter retrieval algorithms are discussed, as well as the synergetic use of satellite observations, model outputs, and in situ data. The need for careful satellite calibration is stressed, and the scaling problem is emphasized. Recent results are reviewed to indicate what the land surface remote sensing problems are and how they might be attacked. Two concrete applications are presented: an “all weather” retrieval of surface skin temperature from combined microwave and infrared observations and a soil moisture analysis from the merging of multisatellite observations and land surface model outputs. This paper is intended to stimulate debates and collaborations between the land surface modelers and the satellite remote sensing community for the design of the next generation of land surface products.

Human genome behaviour: a powerful mechanism for optimizing the use of space technology in surveying networks design

An approach based on the behaviour of human genome is developed to efficiently provide a general framework for optimizing the use of space technology in surveying networks design. The developed approach attempts to apply the successful self-organizing principles based upon the biological evolution to artificial intelligence. It mimics the phenomena of natural selection observed in nature to achieve its goals by continuously adopting a population of candidate solutions and improving its performance over successive generations. The goal of adaptation is to find the best solution that optimizes the design of a surveying network based on the use of satellite observations. This network can be defined as a set of stations, co-ordinated by a series of sessions formed by placing receivers on the stations. The problem is to search for the best order for observing these sessions to give the best observation schedule at minimum cost. The obtained results prove the effectiveness of the developed technique in term of solution quality and computational efforts.

Remote sensing: environmental change

Among the advantages of satellite imagery for geographical research is the ability tocapture in an instant a synoptic view of a large part of the Earth’s surface and to acquirerepeated measurements of the same area on a regular basis. It is precisely theseproperties that make satellite remote sensing such an important source of data forstudies of the dynamics of the Earth’s surface and atmosphere. International researchprogrammes such as the Intergovernmental Panel on Climate Change (IPCC), theInternational Geosphere– Biosphere Programme (IGBP), the World Climate ResearchProgram and the International Human Dimensions Programme on GlobalEnvironmental Change (IHDP) make extensive use of satellite observations because itis possible to derive quantitative measurements of the dynamics of many atmospheric,oceanographic and land surface characteristics. Humans are changing the natural rateof carbon exchange between the Earth’s atmosphere and the terrestrial biospherethrough land use change. Remote sensing can provide an effective tool to examinecarbon stocks and their response to human interference through deforestation, refor-estation, afforestation and other forms of land use change. These data are helping toinform the IPCC to formulate policy responses to climate change (for example theKyoto Protocol) and to monitor policies introduced to mitigate the increased levels ofCO

A rose analysis method relating air chemistry to fire distribution in tropical Africa

Emissions from vegetation fires in the tropics contribute significantly to atmospheric chemistry at continental and global scales. Africa is the continent where the largest number of vegetation fires annually occurs. The use of Global Area Coverage (GAC) data, from the Advanced Very High Resolution Radiometer (AVHRR) sensor onboard the NOAA satellites, allows a good description at continental level of the spatial distribution of intense active fire patterns and a unique temporal perspective over multi-annual periods of time. In this study, 5 years of active fire maps, from November 1984 to October 1989, derived from GAC data for the African continent were considered. In order to enhance the relationships between spatially distributed phenomena, such as regional patterns of active fires, and point data, such as experimental sites of atmospheric chemistry measurements, the rose diagram technique as derived from directional statistics was exploited. This methodological approach allowed the spatial characteristics of vegetation fires, which is considered the main source of atmospheric pollutants in Africa, to be described using measures of frequency and distance for each reference point. Comparison between rose diagrams of fires and nitrate (NO 3 −) content in precipitation as measured at Enyele (Congo), at the heart of the equatorial forest during both dry and wet seasons, confirmed the usefulness of satellite observations and the spatial analysis technique proposed.

Mapping rainfall fields and their ENSO variation in data-sparse tropical south-west Pacific Ocean region

Rainfall fields for the data-sparse tropical south-west Pacific Ocean region have been mapped by partial thin-plate smoothing spline surface modelling applied to island rainfall measurements, enhanced by the use of satellite observations of outgoing longwave radiation (OLR) as a regression covariate. The aim is to obtain spatially realistic rainfall maps, especially in the data-sparse areas between island groups, through a fully objective and statistically valid method that includes error estimates. The method has been applied to the region 4°N–24°S, 168°E–154°W. The rainfall data set initially comprised 57 stations, most with 40 year records. As a first step, a regression of annual OLR and rainfall for atolls only was formed and used to eliminate ‘outlier’ rainfall stations, all of which are on mountainous islands and thus are probably influenced orographically. The maps clearly show the spatial patterns and seasonal behaviour of the region's key meteorological features, namely, the South Pacific Convergence Zone (SPCZ), the southern edge of the Inter-tropical Convergence Zone (ITCZ), and the wedge shaped region of divergent easterlies lying between them. To identify ENSO variations, maps of 3-month seasonal rainfall were constructed from composites of eight El Nino (negative SOI) episodes and nine La Nina (positive SOI) episodes. These maps are relatively rough in appearance, but nevertheless they show the evolution of the spatial patterns through each composite episode and the strong and symmetrically opposite differences between them. Marked variations in the strength and position of the SPCZ are evident and the isohyets in the equatorial dry zone exhibit east–west shifts of nearly 3000 km relative to the average field. The rainfall variation at a particular location may be understood in terms of competition of influence among the changing features of the pattern, rather than as a simple linear function of the SOI. © 1998 Royal Meteorological Society