Estimation of actual carbon dioxide removal in burned forests using satellite data:A case study in South Korea

With the increasing impact of climate change,carbon emissions and removals have become major issues.Forests are major carbon pools,and forest fires are an essential part of the carbon cycle.This study introduces a model for estimating the detailed actual CO_(2)removal in burned forests using burn severity and tree survivability.Actual CO_(2)removal was estimated from empirical yield tables without using the standard carbon removal provided by the national inventory.The primary CO_(2)calculation method followed the guidelines of the International Panel on Climate Change.The burn severity was mapped using Sentinel-2 multispectral instrument data,and the survivability of each forest type was estimated according to burn severity.The survivability was applied to the pre-fire CO_(2)removal of each forest to estimate post-fire CO_(2)removal.In our case study,the burned forest area was 1,034 ha,and the CO_(2)removal before the fire was 8,615.3t/year.After the fire,removal decreased by 81.2%to 1,618.4 t/yr.In particular,the decrease in coniferous forests was high,more than 86%.The lack of survivability data on burned trees was a major limitation of our study.Systematically accumulating field monitoring data of post-fire forests will be necessary for future research and could serve as a reference for devising immediate countermeasures against forest fires.

A global mantle conductivity model derived from 8 years of Swarm satellite magnetic data

Mantle conductivity imaging is one of the scientific goals of the forthcoming Macao Science Satellite-1(MSS-1).To achieve this goal,we develop a data analysis and inversion scheme for satellite magnetic data to probe global one-dimensional(1D)mantle conductivity structures.Using this scheme,we present a new global mantle conductivity model by analyzing over 8 years of Swarm satellite magnetic data.First,after sophisticated data selection procedures and the removal of core and crustal fields,the inducing and induced spherical harmonic coefficients of magnetic potential due to the magnetospheric ring current are derived.Second,satellite Cresponses are estimated from the time series of these coefficients.Finally,the observed responses are inverted for both smooth and threejump conductivity models using a quasi-Newton algorithm.The obtained conductivity models are in general agreement with previous global mantle conductivity models.A comparison of our conductivity model with the laboratory conductivity model suggests the mean state of the upper mantle and transition zone is relatively dry.This scheme can be used to process the forthcoming Macao Science Satellite-1 magnetic data.

Monitoring Land-Use Change in Nakuru (Kenya) Using Multi-Sensor Satellite Data

Recently land-use change has been the main concern for worldwide environment change and is being used by city and regional planners to design sustainable cities. Nakuru in the central Rift Valley of Kenya has undergone rapid urban growth in last decade. This paper focused on urban growth using multi-sensor satellite imageries and explored the potential benefits of combining data from optical sensors (Landsat, Worldview-2) with Radar sensor data from Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) data for urban land-use mapping. Landsat has sufficient spectral bands allowing for better delineation of urban green and impervious surface, Worldview-2 has a higher spatial resolution and facilitates urban growth mapping while PALSAR has higher temporal resolution compared to other operational sensors and has the capability of penetrating clouds irrespective of weather conditions and time of day, a condition prevalent in Nakuru, because it lies in a tropical area. Several classical and modern classifiers namely maximum likelihood (ML) and support vector machine (SVM) were applied for image classification and their performance assessed. The land-use data of the years 1986, 2000 and 2010 were compiled and analyzed using post classification comparison (PCC). The value of combining multi-temporal Landsat imagery and PALSAR was explored and achieved in this research. Our research illustrated that SVM algorithm yielded better results compared to ML. The integration of Landsat and ALOS PALSAR gave good results compared to when ALOS PAL- SAR was classified alone. 19.70 km2 of land changed to urban land-use from non-urban land-use between the years 2000 to 2010 indicating rapid urban growth has taken place. Land-use information is useful for the comprehensive land-use planning and an integrated management of resources to ensure sustainability of land and to achieve social Eq- uity, economic efficiency and environmental sustainability.

Latest Progress of the Chinese Meteorological Satellite Program and Core Data Processing Technologies

In this paper,the latest progress,major achievements and future plans of Chinese meteorological satellites and the core data processing techniques are discussed.First,the latest three FengYun(FY)meteorological satellites(FY-2H,FY-3D,and FY-4A)and their primary objectives are introduced Second,the core image navigation techniques and accuracies of the FY meteorological satellites are elaborated,including the latest geostationary(FY-2/4)and polar-orbit(FY-3)satellites.Third,the radiometric calibration techniques and accuracies of reflective solar bands,thermal infrared bands,and passive microwave bands for FY meteorological satellites are discussed.It also illustrates the latest progress of real-time calibration with the onboard calibration system and validation with different methods,including the vicarious China radiance calibration site calibration,pseudo invariant calibration site calibration,deep convective clouds calibration,and lunar calibration.Fourth,recent progress of meteorological satellite data assimilation applications and quantitative science produce are summarized at length.The main progress is in meteorological satellite data assimilation by using microwave and hyper-spectral infrared sensors in global and regional numerical weather prediction models.Lastly,the latest progress in radiative transfer,absorption and scattering calculations for satellite remote sensing is summarized,and some important research using a new radiative transfer model are illustrated.

Magnetic field data processing methods of the China Seismo-Electromagnetic Satellite

The High Precision Magnetometer(HPM) on board the China Seismo-Electromagnetic Satellite(CSES) allows highly accurate measurement of the geomagnetic field; it includes FGM(Fluxgate Magnetometer) and CDSM(Coupled Dark State Magnetometer)probes. This article introduces the main processing method, algorithm, and processing procedure of the HPM data. First, the FGM and CDSM probes are calibrated according to ground sensor data. Then the FGM linear parameters can be corrected in orbit, by applying the absolute vector magnetic field correction algorithm from CDSM data. At the same time, the magnetic interference of the satellite is eliminated according to ground-satellite magnetic test results. Finally, according to the characteristics of the magnetic field direction in the low latitude region, the transformation matrix between FGM probe and star sensor is calibrated in orbit to determine the correct direction of the magnetic field. Comparing the magnetic field data of CSES and SWARM satellites in five continuous geomagnetic quiet days, the difference in measurements of the vector magnetic field is about 10 nT, which is within the uncertainty interval of geomagnetic disturbance.

Application system and data description of the China Seismo-Electromagnetic Satellite

The China Seismo-Electromagnetic Satellite, launched into orbit from Jiuquan Satellite Launch Centre on February 2 nd, 2018, is China's first space satellite dedicated to geophysical exporation. The satellite carries eight scientific payloads including high-precision magnetometers to detect electromagnetic changes in space, in particular changes associated with global earthquake disasters. In order to encourage and facilitate use by geophysical scientists of data from the satellite's payloads, this paper introduces the application systems developed for the China Seismo-Electromagnetic Satellite by the Institute of Crustal Dynamics, China Earthquake Administration;these include platform construction, data classification, data storage, data format, and data access and acquisition.

FY-3A SATELLITE MICROWAVE DATA ASSIMILATION EXPERIMENTS IN TROPICAL CYCLONE FORECAST

China's new generation of polar-orbiting meteorological satellite FY-3A was successfully launched on May 26,2008,carrying microwave sounding devices which had similar performance to ATOVS of NOAA series.In order to study the application of microwave sounding data in numerical prediction of typhoons and to improve typhoon forecasting,we assimilated data directly for numerical forecasting of the track and intensity of the 2009 typhoon Morakot(0908)based on the WRF-3DVar system.Results showed that the initial fields of the numerical model due to direct assimilation of FY-3A microwave sounding data was improved much more than that due to assimilation of conventional observations alone,and the improvement was especially significant over the ocean,which is always without conventional observations.The model initial fields were more reasonable in reflecting the initial situation of typhoon circulation as well as temperature and humidity conditions,and typhoon central position at sea was also adjusted.Through direct 3DVar assimilation of FY-3A microwave data,the regional mesoscale model improves the forecasting of typhoon track.Therefore,the FY-3A microwave data could efficiently improve the numerical prediction of typhoons.

Observational study of super typhoon Meranti (2016) using satellite, surface drifter, Argo float and reanalysis data

The present work describes the basic features of super typhoon Meranti(2016)by multiple data sources.We mainly focus on the upper ocean response to Meranti using multiplatform satellites,in situ surface drifter and Argo floats,and compare the results with the widely used idealized wind vortex model and reanalysis datasets.The pre-existing meso-scale eddy provided a favor underlying surface boundary condition and also modulated the upper ocean response to Meranti.Results show that the maximum sea surface cooling was 2.0℃after Meranti.The satellite surface wind failed to capture the core structure of Meranti as the idealized wind vortex model deduced.According to the observation of sea surface drifters,the near-inertial currents were significantly enhanced during the passage of Meranti.The temperature and salinity profiles from Argo floats revealed both the mixed-layer extension and subsurface upwelling induced by Meranti.The comparison results show that the sea surface temperature and surface wind in the reanalysis datasets differs from those in remote sensing system.Sea surface cooling is similar in both satellite and in situ observation,and sea surface salinity response has a lower correlation with the precipitation rate.

Double cores of the Ozone Low in the vertical direction over the Asian continent in satellite data sets

Using four satellite data sets(TOMS/SBUV, OMI, MLS, and HALOE), we analyze the seasonal variations of the total column ozone(TCO) and its zonal deviation(TCO*), and reveal the vertical structure of the Ozone Low(OV) over the Asian continent. Our principal findings are:(1) The TCO over the Asian continent reaches its maximum in the spring and its minimum in the autumn. The Ozone Low exists from May to September.(2) The Ozone Low has two negative cores, located in the lower and the upper stratosphere. The lower core is near 30 hPa in the winter and 70 hPa in the other seasons. The upper core varies from 10 hPa to 1 hPa among the four seasons.(3)The position of the Ozone Low in the lower and the upper stratosphere over the Asian continent shows seasonal variability.

Missing Data Imputations for Upper Air Temperature at 24 Standard Pressure Levels over Pakistan Collected from Aqua Satellite

This research was an effort to select best imputation method for missing upper air temperature data over 24 standard pressure levels. We have implemented four imputation techniques like inverse distance weighting, Bilinear, Natural and Nearest interpolation for missing data imputations. Performance indicators for these techniques were the root mean square error (RMSE), absolute mean error (AME), correlation coefficient and coefficient of determination ( R2 ) adopted in this research. We randomly make 30% of total samples (total samples was 324) predictable from 70% remaining data. Although four interpolation methods seem good (producing <1 RMSE, AME) for imputations of air temperature data, but bilinear method was the most accurate with least errors for missing data imputations. RMSE for bilinear method remains <0.01 on all pressure levels except 1000 hPa where this value was 0.6. The low value of AME (<0.1) came at all pressure levels through bilinear imputations. Very strong correlation (>0.99) found between actual and predicted air temperature data through this method. The high value of the coefficient of determination (0.99) through bilinear interpolation method, tells us best fit to the surface. We have also found similar results for imputation with natural interpolation method in this research, but after investigating scatter plots over each month, imputations with this method seem to little obtuse in certain months than bilinear method.

Characteristics of Fengyun-4A Satellite Atmospheric Motion Vectors and Their Impacts on Data Assimilation

The high observation efficiency,scanning speed and observation frequency of the Fengyun-4A(FY-4A)satellite indicates the progress of Chinese geostationary meteorological satellites.The characteristics of FY-4A atmospheric motion vectors(AMVs)derived from the high-level water vapor(WV-High)channel,mid-level water vapor(WV-Mid)channel,and infrared(IR)channel of FY-4A are analyzed,and their corresponding observation errors estimated.Then,the impacts of single-channel and multi-channel FY-4A AMVs on RMAPS-ST(the Rapid-refresh Multi-scale Analysis and Prediction System-Short Term)are evaluated based on one-month data assimilation cycling and forecasting experiments.Results show that the observation errors of FY-4A AMVs from the three channels have an explicit vertical structure.Results from the cycling experiments indicate that the assimilation of AMVs from WV-High produces more apparent improvement of the wind in the upper layer,while a more positive effect in the lower layer is achieved by the assimilation of AMVs from IR.Furthermore,the assimilation of AMVs from IR is more skillful for medium and moderate precipitation than from other channels owing to the good quality of data in the lower layer in the AMVs from IR.Assimilation of FY-4A AMVs from the three channels could combine the advantages of assimilation from each individual channel to improve the wind in the upper,middle and lower layers simultaneously.

A wave energy resource assessment in the China's seas based on multi-satellite merged radar altimeter data

Wave energy resources are abundant in both offshore and nearshore areas of the China's seas. A reliable assessment of the wave energy resources must be performed before they can be exploited. First, for a water depth in offshore waters of China, a parameterized wave power density model that considers the effects of the water depth is introduced to improve the calculating accuracy of the wave power density. Second, wave heights and wind speeds on the surface of the China's seas are retrieved from an AVISO multi-satellite altimeter data set for the period from 2009 to 2013. Three mean wave period inversion models are developed and used to calculate the wave energy period. Third, a practical application value for developing the wave energy is analyzed based on buoy data. Finally, the wave power density is then calculated using the wave field data. Using the distribution of wave power density, the energy level frequency, the time variability indexes, the total wave energy and the distribution of total wave energy density according to a wave state, the offshore wave energy in the China's seas is assessed. The results show that the areas of abundant and stable wave energy are primarily located in the north-central part of the South China Sea, the Luzon Strait, southeast of Taiwan in the China's seas; the wave power density values in these areas are approximately 14.0–18.5 k W/m. The wave energy in the China's seas presents obvious seasonal variations and optimal seasons for a wave energy utilization are in winter and autumn. Except for very coastal waters, in other sea areas in the China's seas, the energy is primarily from the wave state with 0.5 m≤H s≤4 m, 4 s≤T e≤10 s where H s is a significant wave height and T e is an energy period; within this wave state, the wave energy accounts for 80% above of the total wave energy. This characteristic is advantageous to designing wave energy convertors(WECs). The practical application value of the wave energy is higher which can be as an effective supplement for an energy consumption in some areas. The above results are consistent with the wave model which indicates fully that this new microwave remote sensing method altimeter is effective and feasible for the wave energy assessment.

A Case Study of Impact of FY-2C Satellite Data in Cloud Analysis to Improve Short-Range Precipitation Forecast

Chinese FengYun-2C(FY-2C) satellite data were combined into the Local Analysis and Prediction System(LAPS) model to obtain three-dimensional cloud parameters and rain content. These parameters analyzed by LAPS were used to initialize the Global/Regional Assimilation and Prediction System model(GRAPES) in China to predict precipitation in a rainstorm case in the country. Three prediction experiments were conducted and were used to investigate the impacts of FY-2C satellite data on cloud analysis of LAPS and on short range precipitation forecasts. In the first experiment, the initial cloud fields was zero value. In the second, the initial cloud fields were cloud liquid water, cloud ice, and rain content derived from LAPS without combining the satellite data. In the third experiment, the initial cloud fields were cloud liquid water, cloud ice, and rain content derived from LAPS including satellite data. The results indicated that the FY-2C satellite data combination in LAPS can show more realistic cloud distributions, and the model simulation for precipitation in 1–6 h had certain improvements over that when satellite data and complex cloud analysis were not applied.

Retrieval of Atmospheric Horizontal Visibility by Statistical Regression from NOAA/AVHRR Satellite Data

Based on the atmospheric horizontal visibility data from forty-seven observational stations along the eastern coast of China near the Taiwan Strait and simultaneous NOAA/AVHRR multichannel satellite data during January 2001 to December 2002, the spectral characters associated with visibility were investigated. Successful retrieval of visibility from multichannel NOAA/AVHRR data was performed using the principal component regression (PCR) method. A sample of retrieved visibility distribution was discussed with a sea fog process. The correlation coefficient between the observed and retrieved visibility was about 0.82, which is far higher than the 99.[KG-*7]9% confidence level by statistical test. The rate of successful retrieval is 94.98% of the 458 cases during 2001-2002. The error distribution showed that high visibilities were usually under-estimated and low visibilities were over-estimated and the relative error between the observed and retrieved visibilities was about 21.4%.

Estimation of water balance in the source region of the Yellow River based on GRACE satellite data

Water storage has important significance for understanding water cycles of global and local domains and for monitoring climate and environmental changes.As a key variable in hydrology,water storage change represents the sum of precipitation,evaporation,surface runoff,soil water and groundwater exchanges.Water storage change data during the period of 2003-2008 for the source region of the Yellow River were collected from Gravity Recovery and Climate Experiment(GRACE)satellite data.The monthly actual evaporation was estimated according to the water balance equation.The simulated actual evaporation was significantly consistent and correlative with not only the observed pan(20 cm)data,but also the simulated results of the version 2 of Simple Biosphere model.The average annual evaporation of the Tangnaihai Basin was 506.4 mm,where evaporation in spring,summer,autumn and winter was 130.9 mm,275.2 mm,74.3 mm and 26.1 mm,and accounted for 25.8%,54.3%,14.7% and 5.2% of the average annual evaporation,respectively.The precipitation increased slightly and the actual evaporation showed an obvious decrease.The water storage change of the source region of the Yellow River displayed an increase of 0.51 mm per month from 2003 to 2008,which indicated that the storage capacity has significantly increased,probably caused by the degradation of permafrost and the increase of the thickness of active layers.The decline of actual evaporation and the increase of water storage capacity resulted in the increase of river runoff.

Using Satellite Data to Analyze the Initiation and Evolution of Deep Convective Clouds

In this study, two deep convective cloud cases were analyzed in detail to study their initiation and evolution. In both cases, all deep convective clouds were positioned at the rear of the cold front cloud bands and propagated backward. Satellite data showed that prior to initiation of the deep convective clouds, thermodynamic and moist conditions were favorable for their formation. In the morning, a deep convective cloud at the rear of cold front cloud band propagated backward, the outflow boundary of which created favorable conditions for initiation. An additional deep convective cloud cluster moved in from the west and interacted with the outflow boundary to develop a mesoscale convective system(MCS) with large, ellipse-shaped deep convective clouds that brought strong rainfall. The initiation and evolution of these clouds are shown clearly in satellite data and provide significant information for nowcasting and short-term forecasting.

Assimilation of Feng-Yun-3B Satellite Microwave Humidity Sounder Data over Land

The ECMWF has been assimilating Feng-Yun-3B(FY-3B) satellite microwave humidity sounder(MWHS) data over ocean in an operational forecasting system since 24 September 2014. It is more difficult, however, to assimilate microwave observations over land and sea ice than over the open ocean due to higher uncertainties in land surface temperature, surface emissivity and less effective cloud screening. We compare approaches in which the emissivity is retrieved dynamically from MWHS channel 1 [150 GHz(vertical polarization)] with the use of an evolving emissivity atlas from 89 GHz observations from the MWHS onboard NOAA and EUMETSAT satellites. The assimilation of the additional data over land improves the fit of short-range forecasts to other observations, notably ATMS(Advanced Technology Microwave Sounder) humidity channels, and the forecast impacts are mainly neutral to slightly positive over the first five days. The forecast impacts are better in boreal summer and the Southern Hemisphere. These results suggest that the techniques tested allow for effective assimilation of MWHS/FY-3B data over land.

An experimenal analysis for the impact of 2D variation assimilation of satellite data on typhoon track simulation

A series of test simulations are performed to evaluate the impact of satellite-derived meteorological data on numerical typhoon track prediction. Geostationary meteorological satellite (GMS-5) and NOAA’s TIROS operational vertical sounder (TOVS) observations are used in the experiments. A two-dimensional variation assimilation scheme is developed to assimilate the satellite data directly into the Penn State-NCAR nonhydrostatic meteorological model (MM5). Three-dimensional objective analyses fields based on T213 results and routine observations are employed as the background fields of the initialization. The comparisons of the simulated typhoon tracks are also carried out, which correspond respectively to the initialization scheme with two-dimensional variation(2D-Var), three-dimensional observational nudging and direct assimilation of satellite data. It is found that, comparing with the experiments without satellite data assimilation, the first two assimilation schemes lead to significant improvements on typhoon track prediction. Track errors reduce by 18% at 12 h for 2D-Var and from about 16% at 24 h to about 35% at 48 h for observational nudging. The simulated results based on assimilating different kinds of satellite data are also compared .

A preliminary study of level 1A data processing of a low-low satellite to satellite tracking mission

With the Gravity Recovery and Climate Experiment(GRACE)mission as the prime example,an overview is given on the management and processing of Level 1A data of a low-low satellite to satellite tracking mission.To illustrate the underlying principle and algorithm,a detailed study is made on the K-band ranging(KBR)assembly,which includes the measurement principles,modeling of noises,the generation of Level 1A data from that of Level0 as well as Level 1A to Level 1B data processing.

Compression Design and Test of Water Vapor Receiving Data by Beidou Satellite

Water vapor monitoring system by Beidou satellite is a new detection system in meteorological department,which makes receiving amount of detected data and data storage and transmission pressure increase. Here,we try to use data compression to relieve pressure. Compression software of water vapor monitoring system by Beidou satellite can be designed into three components: real-time compression software,check compression software and manual compression software,which respectively completes the compression tasks under real-time receiving,in-time check and separate compression,thereby forming a perfect compression system. Taking the design of manual compression software as guide,and using c language to develop,compression test of original receiving data is conducted. Test result proves that the system can carry out batch automatic compression,and compression rate can reach 30%,which can reach the target of saving space in a degree.