Li et al. (2007) used measurements from the DefenseMeteorologicalSatelliteProgram (DMSP) and ROCSAT- 1 satellites during a period of three years (2000–2002) near solar maximum to investigate the longitudinal/sea- sonal dependence of plasma bubble occurrence on the postsunset vertical plasma drift. The DMSP satellites had polar orbits at 840 km. The ROCSAT-1 satellite was in a circular orbit at 600 km with an orbit inclination of 35 o . The occurrence of ESF was identified from ion density data when σ, defined by Equation (1), is larger than 0.3%. For DMSP data, the vertical ion drift mea- sured at ~1800 LT was used to represent the PRE. For ROCSAT-1 data, the vertical ion drift between 1800 and 1900 LT was used to represent the PRE. In both DMSP and ROCSAT-1 data, the mean value of vertical drift vel- ocities within ±5 o from the magnetic equator is used to represent the vertical drift over the magnetic equator. The PRE value used in this study was not the peak drift of the PRE. It was found that the longitudinal/seasonal variations of plasma bubbles occurrence are similar to those of the PRE and that higher occurrence of plasma bubbles is related to larger PRE values. It was suggested that the occurrence probability of equatorial plasma bubbles is closely related to the pre-reversal E × B drift.
The third step is to determine the mechanism of the EQ-related ionosphere disturbance. Reasonable mecha- nisms of ionosphere disturbance are far more difficult to identify because no systematic morphology of iono- sphere modification has been established regarding latitude, longitude, and local time. The probable source seems to be an electric field. There is supporting evi- dence for this such as atmosphere glow and spontane- ous switching off of televisions (Ikeya 2004). Moreover, EQ-related ionosphere disturbances are found at conju- gate points as well. Recently, we found from the DefenseMeteorologicalSatelliteProgram (DMSP) data in the US that mid-latitude trough moves equatorward during EQ preparation times, and density of atomic oxygen ion O +
Today's U.S. space programs trace back to the Department of Defense (DoD) rocket, sensor, and satellite development projects that began in the decade following World War II. With little theory and very little experience available to guide these projects, DoD's development teams learned their space trade on the job, often resulting from analyses of catastrophic failures. Early on, DoD developed instruments to measure meteorological parameters needed to determine the atmospheric conditions that the rockets were encountering as they were propelled to then extraordinary altitudes. These measurements, recovered from salvaged recorders or from radio transmissions, were the basis for meteorological research. Still cameras became part of the payload and recovered film depicted images of the Earth’s surface and cloud cover from space. These first ventures into "Earth remote sensing" from rockets were practical and efficient ways to gather environmental data that was critical to advancing the United States space efforts and provided a perspective from space and near space. These images gave investigators views of the patterns imbedded into an environmental infrastructure.
and instrument to map floods for several hundreds of loca- tions for the Global Disaster Alert and Coordination System. While visible and shortwave-infrared bands often provide sub-kilometer resolution for inundation mapping, their capa- bility is very limited in a cloudy sky. This limitation is usu- ally very restrictive over prone-to-flooding watersheds and deltas in tropical regions with a high-frequency of heavy pre- cipitation events. For instance, a long-term analysis of Land- sat data revealed that due to cloud contamination, only 30 % of overpasses are useful for inundation mapping (Melack et al., 1994). Because of this limitation, most of the related satellite products, including the MODIS inundation prod- ucts, are available mostly in monthly, seasonal, and/or an- nual timescales (Ordoyne and Friedl, 2008). However, mi- crowaves can penetrate clouds – and to some extent hy- drometeors in frequencies ≤ 37 GHz – to provide water in- undation mapping in almost all weather conditions. Unfortu- nately, due to the coarse resolution of microwave data, e.g., (47 ×74) km 2 at 19 GHz to (13 ×16) km 2 at 183 GHz for the SSMIS), only large water bodies can be detected and sub- pixel inundated areas cannot be directly identified (Smith, 1997). Presently, there exist several sensors on board dif- ferent satellites that overlap in the spatial and time domains that sample land–atmosphere signals at different wavelengths of the electromagnetic spectrum. Therefore, it is impera- tive to integrate these multi-sensor observations to overcome their individual shortcomings and improve retrievals of land– atmosphere parameters and the extent of flooded areas (Pri- gent et al., 2001, 2007; Crétaux et al., 2011; Temimi et al., 2011; Schroeder et al., 2010).
Meteorological data had to be obtained from a diﬀerent location since CUSV is not equipped with meteo sensors. Thus, two meteo stations were identiﬁed in the CUSV vicinity (Fig. 1). One station belongs to Thai Meteorological Department (TMD) and is located about 3.3 km from the campus. The other station belongs to Thai Red Cross (TRC) and is located about 1.7 km from the campus. The TMD station provided meteo parameters (pressure, temperature, and rainfall) at three-hour temporal resolution starting from 01:00AM. The TMD data was available for the entire year. We used these data to compute PWV estimates. In addition, the TRC station provided same meteo parameters but at higher resolution, i.e. 5-min intervals. Unfortunately, TRC data was available only between Jun-Nov 2016. We used these data to study the correlation between the PWV estimates and actual rainfall logs.
gated agriculture in CA is mainly fed by the stream water di- version with only a small portion of groundwater withdrawal (FAO, 2013; Siebert et al., 2010). Hence, reliable predic- tion of seasonal runoff during the vegetation period (April– September) is crucial for agricultural planning and yield es- timation in the low-lying countries in the Aral Sea basin, as well as for the management of reservoir capacities including dam safety operations in the upper parts of the catchments. Seasonal forecasts are one of the major responsibilities of the hydro-meteorological (hydromet) services of the CA coun- tries and are regularly released starting in January and con- tinuing until June, with the primary forecast issued at the end of March–beginning of April for the upcoming 6-month pe- riod. In some post-Soviet countries, these forecasts are typi- cally developed based on empirical relationships for individ- ual basins relating precipitation, temperature and snow depth and snow water equivalent (SWE) records to seasonal dis- charge, partly available only in analogue form as look-up ta- bles or graphs (hydromet services, unpublished questionnaire survey undertaken within the CAWa project, http://www. cawa-project.net). Particularly, point measurements of snow depth and/or snow water equivalent, which have been car- ried out by helicopter flights or footpath surveys in mountain regions in recent decades, are costly or not feasible due to ac- cess problems nowadays. Other hydromet services apply the hydrological forecast model AISHF (Agaltseva et al., 1997), developed at the Uzbek hydro-meteorological service (Uzhy- dromet), which computes discharge hydrographs by consid- ering temperature, snow accumulation, and snow melt. Snow pack is accumulated in winter and temperature and precipi- tation are taken from an analogous year to drive the model in the forecast mode. The hydro-meteorological services rely on meteorological and hydrological data acquired by the network of climate and discharge stations, which, however, strongly diminished during the 1990s (Unger-Shayesteh et al., 2013). Fortunately the density of the monitoring network recovers nowadays, partly with substantial international sup- port (e.g. Schöne et al., 2013; CAHMP Programme by World Bank; previous programmes by SDC and USAID), but at a slow rate. In any case, the hydro-meteorological services need timely to near-real-time data and simple methodologies capable of utilizing available information in order to fulfil their mandatory tasks.
Abstract. Hurricanes, as one of the most devastating natural hazards, have posed a great threat to people in coastal ar- eas. A better understanding of the spatiotemporal dynamics of human settlement in hurricane-prone areas largely bene- fits sustainable development. This study uses the nighttime light (NTL) data from the DefenseMeteorological Satel- lite Program’s Operational Linescan System (DMSP/OLS) to examine human settlement development in areas with different levels of hurricane proneness from 1992 to 2013. The DMSP/OLS NTL data from six satellites were intercali- brated and desaturated with the Advanced Very High Resolu- tion Radiometer (AVHRR) and Moderate Resolution Imag- ing Spectroradiometer (MODIS) optical imagery to derive the Vegetation Adjusted NTL Urban Index (VANUI), a pop- ular index that quantifies human settlement intensity. The derived VANUI time series was examined with the Mann– Kendall test and Theil–Sen test to identify significant spa- tiotemporal trends. To link the VANUI product to hurricane impacts, four hurricane-prone zones were extracted to repre- sent different levels of hurricane proneness. Aside from geo- graphic division, a wind-speed-weighted track density func- tion was developed and applied to historical storm tracks which originated in the North Atlantic Basin to better cat- egorize the four levels of hurricane proneness. Spatiotempo- ral patterns of human settlement in the four zones were fi- nally analyzed. The results clearly exhibit a north–south and inland–coastal discrepancy of human settlement dynamics. This study also reveals that both the zonal extent and zonal increase rate of human settlement positively correlate with hurricane proneness levels. The intensified human settlement
Software operating characteristic data acquisition range contained 182 sets of polar orbit meteorologicalsatellite data processing software for 12 kinds of in- struments. Polar orbit meteorological satellites carried remote sensing instru- ment. Its mode of operation is to collect data on a regular basis and download the collected data to the ground station. The software needs to run multiple times per day (each run is called a track). Data acquisition environment is the simulation environment and acquisition time is 4 days. The collection method for operating characteristics of the software is to force each weather processing software running in serial (the actual environment running is in parallel), so that each software can get sufficient hardware resources and give full play to software performance. Software operating characteristics data acquisition types included CPU, system, process, and job level data, with CPU-level and system-level acqui- sition cycles of 1 second. Job-level data acquisition fields are the main software start time, end time and the located server. System-level data acquisition fields are CPU system and disk wait for usage, CPU idle usage, memory usage, virtual memory usage, disk read and write rates, network receive and send rate. CPU- level data acquisition field has the core CPU system utilization and idle utiliza- tion.
events of recent years occurred, dubbed the “Beast from the East”, with temperatures struggling to rise above freezing as bitterly cold easterly winds swept over the country (Met Éireann, 2019). These two extremes, climate-stress events highlighted the agricultural vulnerability of the country. Almost all of Ireland was negatively impacted, and in particular eastern agricultural regions produced between 5 and 10% less grass than normal in 2018 - equivalent to about 1 ton/ha less (Fig. 1). Figure 2 shows the colour of the vegetation in Ireland in July 2017 compared to July 2018, as measured by NASA TERRA’s satellite. The green fields in July 2017 are desiccated and brown in July 2018 which resulted in a reduction in agricultural production.
The variable effectiveness of soil moisture assimilation has been previously reported in literature. Whereas some studies found improvements (Draper et al., 2011; Wanders et al., 2014b), others obtained mixed or unsatisfactory re- sults (Crow et al., 2005). The scale of soil moisture obser- vations, the dominant runoff processes in the study basin and the model structure and parameter uncertainties may partly explain this variability. In this particular study, the novel use of a finer-spatial-resolution satellite soil moisture prod- uct together with the climate and hydrogeological character- istics of the catchment could be a possible explanation of the positive impact of soil moisture assimilation. Renzullo et al. (2014) assimilated satellite soil moisture observations from multiple sensors (ASCAT and AMSR-E) obtained at scales coarser than the model (AWRA-L) resolution. In the present study, the scale of soil moisture observations coin- cides with the model scale. A specific analysis of the impact on streamflow and soil moisture estimates of assimilating non-downscaled AMSR-E soil moisture assimilation could be a possible route to further investigate the effect of dif- ferent spatial-resolution soil moisture products. To this end, AMSR-E soil moisture observations at the original spatial resolution were assimilated into PCR-GLOBWB and results analysis presented in this study were reproduced. Results showed that the assimilation of non-downscaled soil mois- ture observations has a positive impact on soil moisture and
Dakhla, a major oasis in the Western Desert of Egypt (Figure 1), is located on low-level ground, at 0 to 200 m above sea level. The aridity index used by the United Nations Environment Program  indicates that this dis- trict lies in a hyperarid region, with annual rainfall of nearly 0 mm. Consequently, the surrounding area is bare of vegetation, except for very isolated clumps of Acacia or Tamarix that survive on the shallow moisture held in blown sand, and moisture from dew, isolated showers, and frontal storms . The climate of Dakhla is con- trolled mainly by the Harmattan, which is a hot wind resulting from high pressure in the Sahara. Although wind directions are mostly north, a slight westerly skewing of the maximum probably reflects topographic in draft of northern winds into the Dakhla depression .
fluxes (Bousquet et al. 2000). The integration of in situ meteorological measurements (Houser et al. 2003) and different satellite remote sensing sources of information (Van den Hurk 2001, Calvet and Noilhan 2000) will be made by implementing and using assimilation techniques in global land surface models. The carbon observatory will collect the remote sensing products provided by the geoland core service “Geo- Biophysical Parameters” and the atmospheric forcing provided by ECMWF. In order to integrate the existing approaches and to deliver an assessment based on independent modelling results, two land surface models will be used: 1) an operational scheme (ECMWF) used in numerical weather forecast models, modified to describe an interactive vegetation (based on ISBA-A-gs, Météo-France); 2) a carbon-water- energy land surface scheme, fitted with carbon dynamics in biomass and soil pools, and with ecosystem dynamics (LSCE). The two models were used in numerous studies and validated against both in situ (e.g. eddy covariance towers) and global datasets (e.g. satellite maps of biophysical variables) but they were developed independently. A method to assimilate remote sensing products will be designed and evaluated based on existing field campaigns devoted to the assimilation of multi-spectral satellite data. The assimilation system will then be run at the global scale with both carbon models. The assimilated output fields will be checked against global observations of different nature, such as eddy covariance networks, long term ecological time series (e.g. IGBP transects), forest and soil carbon inventories, or satellite products that were not used at first in the assimilation procedure. At the end of this project, ECMWF will be able to propose a single near-operational system based on components of the two approaches. The end- product of the system will be a near real-time analysis of biospheric CO 2 fluxes, released by ECMWF
Himawari-8 is the Japanese GEO meteorologicalsatellite (Bessho et al., 2016), which was successfully launched in October 2014. It has 16 observation bands, including three visible bands: blue (0.47 µm), green (0.51 µm), and red (0.64 µm). In the initial survey for PMCs, we used full-disk images in Portable Network Graphics (PNG) format, gener- ated from the level-1a data, Himawari Standard Data (HSD). The PNG full-disk image is a true-color image, i.e., a com- posite of the three visible bands. Each color has an 8 bit resolution (i.e., values ranging from 0 to 255), describing emission intensities from 0 to 641.5092 W m −2 sr −1 µm −1 for the blue band, from 0 to 601.9766 W m −2 sr −1 µm −1 for the green band, and from 0 to 519.3457 W m −2 sr −1 µm −1 for the red band. The color value has a linear relation with the emission intensity for each band. The PNG full-disk im- age has a spatial resolution of ∼ 1 km and is obtained every 10 min. The geometric accuracy of the images is typically less than 0.6 km, i.e., less than the ∼ 1 km spatial resolution. More detailed information for the PNG images can be found in Bessho et al. (2016). For the present survey, we collected a year of PNG images for 2016, and focused our attention on the Earth’s limb region, namely the middle and upper atmo- spheric regions.
throughout the world. Goodberlet et al . developed the D-matrix algorithm, and carried out relevant research. Studies similar to mmwave imaging have also been performed in China. In Reference 12, Laurence N Connor and Paul S Chang adopted a TMI radiometer containing channel of 10.7 GHz on the TRMM satel- lite, and achieved a good effect. However, due to the settings of the medium-low latitude orbit of TRMM satellite, it was difficult for the satellite to obtain the global sea surface wind speed, and its wide application is limited. Based on the research of Jin Yaqiu et al ., it can be observed that the heat radiation effect re- ceived by the microwave radiometer  tends to saturate due to the disturbance from the foam scattering layer in strong wind areas. Therefore, the disturbance from the sea surface foam layer in the natural world is a major problem in wind inversion.
4.5. Provide periodic, mandatory education and training in EO and human relations at installation and fleet unit commands, during pre-commissioning programs and initial entry training, and throughout professional military education (PME) systems, as part of the overall effort to achieve EO within the Department of Defense. This training shall be provided to all Service members, enlisted and officer, including flag and general officers. The training shall include comprehensive material on leadership roles and responsibilities for EO programs, complaints processing, legal implications, reprisal prevention and detection, climate assessment methodologies, and managing civilian equal employment opportunity (EEO) systems.
reasonably be met because the state incentive cannot be deemed the primary or determining factor in the federal government’s or private business’ decision to engage in a defense or space flight contract. In regard to the QDSC program, this assertion fails because the businesses engaged in applying for the incentive are not making job creation or retention decisions based solely on the award of the incentive. These businesses are engaged in bidding for a variety of federal and/ or private procurement contracts, and this bidding likely would not cease if the incentive was not offered. In this regard, businesses are still engaged in bidding for federal contracts even though the QDSC program expired in 2014. While the QDSC award reduces a business’ operating costs and allows for a more competitive bid, it is likely the incentive is paying for jobs that would have been created or retained in the state anyway.
Over recent decades, most research focused on land degra- dation has been based on remote sensing and Earth obser- vation techniques. Much of these investigations have aimed to refine methodological issues in order to accurately track land degradation in vulnerable areas, reduce uncertainties and explain inconsistencies among studies. For instance, a wide array of satellite-derived data, such as vegetation in- dices, normalized surface reflectance, brightness temperature or biomass net primary production derivatives (Mbow et al., 2015), have been utilized to appraise desertification effects in the Sahel (Mbow et al., 2015; Fensholt et al., 2013) and also in other African countries such as Kenya (Omuto, 2011), Somalia (Omuto et al., 2010), South Africa (Thompson et al., 2009) or Zimbabwe (Prince et al., 2009). Likewise, de- sertification in the Mediterranean region has been studied through satellite imagery in Greece (Bajocco et al., 2012), Israel (Shoshany and Karnibad, 2015) and the Iberian Penin- sula (del Barrio et al., 2010). However, although drylands’ key role in the global carbon (C) balance has been demon- strated (Poulter et al., 2014; Ahlström et al., 2015), very few investigations have directly quantified how land degra- dation processes disturb the C sequestration capacity of dry- lands (Lal, 2001), despite it being one of the most important ecosystem services (Watanabe and Ortega, 2011).
Based on the conventional meteorological data and the NCEP/NCAR 1˚ × 1˚ reanalysis data and those related to mid-scale automatic station, satellite cloud picture and radar return, with the dynamic diagnosis analysis method, an analysis is made on the process of the convective rainstorm of quasi-stationary front triggered by the weak cold air on June 4-7, 2014, showing: 1) the process occurred in the event of convection of a stationary front triggered by the eastward moving south trough and the southward moving weak cold air from west under the background of circulation of two ridges and one trough at the Asian-European mid-high latitude and weakening and southeastward moving subtropical high; 2) a system configuration that contributes to convective rainstorms formed in the event of the convergence of low-level moisture, up- per-level divergence and the continuous vertical ascending motion after the 200 hPa upper-level jet stream moved westwards from east and the 850 hPa southwest jet stream intensified; 3) after the intrusion by weak cold air of the meso-scale katallobaric area formed by the accumulated warm moist air of Guangxi before the intrusion, the warm moist air rose to trigger convection; convection cells developed and spread nearby the boundary between anallo- baric area and katallobaric area, during which total 5 MCSs developed and each formed a rainstorm center at the part where the MCSs coincide; a me- so-scale katallobaric area forms and develops 2 - 5 hours earlier than convec- tion, so that it is also a warning of heavy rains.
Only a few previous studies have evaluated the rural environment in North Korea given that it is logistically and politically difficult to acquire scientific information on the productivity of paddy rice of the nation. Remote sens- ing, as advocated in this study, is considered as an efficient approach to monitor spatial regions that are largely inaccessible, and thus, applied to enhance the practical benefits of collecting such data to develop novel mech- anisms that strengthen agricultural precision to addressing socio-economic issues. This study has successfully simulated the paddy productivity in North Korea using satellite-based biophysical and meteorological parameters employing the GRAMI-rice model. In summary, simulated rice yield statistically corresponded to the observed rice yield with a statistically significant range of accuracy according to t-tests (for Cheorwon at p = 0.183, in Paju at p = 0.075, and in NK at p = 0.101).
the atmospheric delay (Ao et al., 2009) is also calculated on board the GNOS. The baseband signal is then sampled at a rate of 100 Hz. For the COSMIC and MetOp missions, the sampling rate of open-loop tracing is 50 Hz (Sokolovskiy, 2001; Sokolovskiy et al., 2007, 2009) and 1000 Hz (von En- geln et al., 2009), respectively. The performance of the COS- MIC mission proves that a 50 Hz open-loop sampling rate is sufficient to monitor the troposphere (Sokolovskiy, 2001; Sokolovskiy et al., 2007, 2009), while MetOp uses 1000 Hz to do a detailed spectrum analysis of the lower troposphere. Indeed, the higher the sampling rate, the more detailed the atmospheric information that can be obtained. Compliant with the FY-3C satellite downlink capability, FY-3C GNOS adopts a 100 Hz open-loop sampling rate, which is proven to be sufficient to capture the signals modulated by the at- mosphere dynamics and uncertainties of the Doppler model. The designed parameters of FY-3C GNOS are summarized in Table 1; it can be seen that some parameters of the FY-3C GNOS are comparable to those of COSMIC (Rocken et al., 2000) or MetOp/GNSS Receiver for Atmospheric Sounding (GRAS; Loiselet et al., 2000).