An Algorithm for Retrieving Precipitable Water Vapor over Land Based on Passive Microwave Satellite Data

Precipitable water vapor (PWV) is one of the most variable components of the atmosphere in both space and time. In this study, a passive microwave-based retrieval algorithm for PWV over land without land surface temperature (LST) data was developed. To build the algorithm, two assumptions exist: (1) land surface emissivities (LSE) at two adjacent frequencies are equal and (2) there are simple parameterizations that relate transmittance, atmospheric effective radiating temperature, and PWV. Error analyses were performed using radiosonde sounding observations from Zhangye, China, and CE318 measurements of Dalanzadgad (43°34′37′′N, 104°25′8′′E) and Singapore (1°17′52′′N, 103°46′48′′E) sites from Aerosol Robotic Network (AERONET), respectively. In Zhangye, the algorithm had a Root Mean Square Error (RMSE) of 4.39 mm and a bias of 0.36 mm on cloud-free days, while on cloudy days there was an RMSE of 4.84 mm and a bias of 0.52 mm because of the effect of liquid water in clouds. The validations in Dalanzadgad and Singapore sites showed that the retrieval algorithm had an RMSE of 4.73 mm and a bias of 0.84 mm and the bigger errors appeared when the water vapor was very dry or very moist.</jats:p

BDS GNSS for Earth Observation

For millennia, human communities have wondered about the possibility of observing phenomena in their surroundings, and in particular those affecting the Earth on which they live. More generally, it can be conceptually defined as Earth observation (EO) and is the collection of information about the biological, chemical and physical systems of planet Earth. It can be undertaken through sensors in direct contact with the ground or airborne platforms (such as weather balloons and stations) or remote-sensing technologies. However, the definition of EO has only become significant in the last 50 years, since it has been possible to send artificial satellites out of Earth’s orbit. Referring strictly to civil applications, satellites of this type were initially designed to provide satellite images; later, their purpose expanded to include the study of information on land characteristics, growing vegetation, crops, and environmental pollution. The data collected are used for several purposes, including the identification of natural resources and the production of accurate cartography. Satellite observations can cover the land, the atmosphere, and the oceans. Remote-sensing satellites may be equipped with passive instrumentation such as infrared or cameras for imaging the visible or active instrumentation such as radar. Generally, such satellites are non-geostationary satellites, i.e., they move at a certain speed along orbits inclined with respect to the Earth’s equatorial plane, often in polar orbit, at low or medium altitude, Low Earth Orbit (LEO) and Medium Earth Orbit (MEO), thus covering the entire Earth’s surface in a certain scan time (properly called ’temporal resolution’), i.e., in a certain number of orbits around the Earth. The first remote-sensing satellites were the American NASA/USGS Landsat Program; subsequently, the European: ENVISAT (ENVironmental SATellite), ERS (European Remote-Sensing satellite), RapidEye, the French SPOT (Satellite Pour l’Observation de laTerre), and the Canadian RADARSAT satellites were launched. The IKONOS, QuickBird, and GeoEye-1 satellites were dedicated to cartography. The WorldView-1 and WorldView-2 satellites and the COSMO-SkyMed system are more recent. The latest generation are the low payloads called Small Satellites, e.g., the Chinese BuFeng-1 and Fengyun-3 series. Also, Global Navigation Satellite Systems (GNSSs) have captured the attention of researchers worldwide for a multitude of Earth monitoring and exploration applications. On the other hand, over the past 40 years, GNSSs have become an essential part of many human activities. As is widely noted, there are currently four fully operational GNSSs; two of these were developed for military purposes (American NAVstar GPS and Russian GLONASS), whilst two others were developed for civil purposes such as the Chinese BeiDou satellite navigation system (BDS) and the European Galileo. In addition, many other regional GNSSs, such as the South Korean Regional Positioning System (KPS), the Japanese quasi-zenital satellite system (QZSS), and the Indian Regional Navigation Satellite System (IRNSS/NavIC), will become available in the next few years, which will have enormous potential for scientific applications and geomatics professionals. In addition to their traditional role of providing global positioning, navigation, and timing (PNT) information, GNSS navigation signals are now being used in new and innovative ways. Across the globe, new fields of scientific study are opening up to examine how signals can provide information about the characteristics of the atmosphere and even the surfaces from which they are reflected before being collected by a receiver. EO researchers monitor global environmental systems using in situ and remote monitoring tools. Their findings provide tools to support decision makers in various areas of interest, from security to the natural environment. GNSS signals are considered an important new source of information because they are a free, real-time, and globally available resource for the EO community

A review of high impact weather for aviation meteorology

This review paper summarizes current knowledge available for aviation operations related to meteorology and provides suggestions for necessary improvements in the measurement and prediction of weather-related parameters, new physical methods for numerical weather predictions (NWP), and next-generation integrated systems. Severe weather can disrupt aviation operations on the ground or in-flight. The most important parameters related to aviation meteorology are wind and turbulence, fog visibility, aerosol/ash loading, ceiling, rain and snow amount and rates, icing, ice microphysical parameters, convection and precipitation intensity, microbursts, hail, and lightning. Measurements of these parameters are functions of sensor response times and measurement thresholds in extreme weather conditions. In addition to these, airport environments can also play an important role leading to intensification of extreme weather conditions or high impact weather events, e.g., anthropogenic ice fog. To observe meteorological parameters, new remote sensing platforms, namely wind LIDAR, sodars, radars, and geostationary satellites, and in situ instruments at the surface and in the atmosphere, as well as aircraft and Unmanned Aerial Vehicles mounted sensors, are becoming more common. At smaller time and space scales (e.g., < 1 km), meteorological forecasts from NWP models need to be continuously improved for accurate physical parameterizations. Aviation weather forecasts also need to be developed to provide detailed information that represents both deterministic and statistical approaches. In this review, we present available resources and issues for aviation meteorology and evaluate them for required improvements related to measurements, nowcasting, forecasting, and climate change, and emphasize future challenges

A new dynamic approach for statistical optimisation of GNSS radio occultation bending angles

Climate change has become a serious issue for our society. It is of great importance to accurately monitor climate change and provide reliable information to the society so that proper actions can be taken to alleviate the significant change of climate. Global Navigation Satellite Systems (GNSS) based radio occultation (RO) is a new satellite remote sensing technique that can provide high vertical resolution, long-term stable and global coverage atmospheric profiles of the Earth’s atmosphere. However, the quality of the retrieved atmospheric profiles decreases above about 30 km due to a low signal-to-noise ratio of GNSS signals at these high altitudes, since errors in bending angle profiles are propagated to refractivity profiles through an Abel integral and subsequently propagated to other atmospheric profiles through the hydrostatic integral. It is therefore important to carefully initialise the bending angles at high altitudes to minimise these error propagation effects and thereby optimise the climate monitoring utility of the retrieved profiles. Statistical optimisation is a commonly used method for this purpose. This method combines the observed bending angle profile and background bending angle profile based on their error covariance matrices to determine “optimised” bending angle profile. The focus of this thesis is to investigate an advanced statistical optimisation algorithm, which dynamically estimates both background and observation error covariance matrices, for the best determination of RO optimised bending angle profile. In this new algorithm, background bending angle profiles and their associated error covariance matrices are estimated using bending angles from multiple days of the European Centre for Medium-range Weather Forecasts (ECMWF) short-term (24h) forecast and analysis fields as well as the averaged observed bending angle. The background error matrices are constructed with geographically varying background error estimates on a daily-updated basis. The observation error covariance matrices are estimated using multiple days of RO data with geographically varying observation errors for an occultation event. The most distinctive advantage of the new algorithm is that both background and observation error covariance matrices are realistically estimated using large ensemble of climatological and observed data, while existing algorithms use crude formulations to estimate both error matrices. The new algorithm developed is evaluated against the algorithm used by the Wegener Center Occultation Processing System version 5.4 (OPSv5.4) by calculating statistical errors of retrieved atmospheric profiles relative to their reference profiles. Since the background errors at different heights are highly correlated and their covariance matrix is critical for the resulting optimised bending angles, the dynamically estimated background error covariance matrix is first used in statistical optimisation to retrieve atmospheric profiles from simulated MetOp as well as observed CHAMP and COSMIC RO events on single days. The dynamically estimated observation error covariance matrix is then used in the statistical optimisation together with the estimated background error covariance matrix to retrieve atmospheric profiles using the same test data. It can be concluded from the evaluation that if the estimated background error covariance matrix is solely used for the statistical optimisation, it can significantly reduce random errors and generate less or similar residual systematic errors (biases) in the optimised bending angles. The subsequent refractivity profiles and atmospheric (dry temperature) profiles retrieved are benefitted from the improved error characteristics of bending angles. If both observation and background error covariance matrices estimated from the new approach are used, the standard deviations of the optimised bending angles are only further reduced for simulated MetOp data, while for the observed CHAMP and COSMIC data, large random errors of bending angles are found at higher altitudes (e.g. &amp;gt; 50 km). This is likely to be that the observation errors are underestimated at high altitudes, where bending angles are largely affected by ionospheric effects and observation errors, and more weights are given to the noisy observed bending angles in the estimation of the optimised bending angles. Errors in CHAMP and COSMIC observed bending angles are further transferred downwards to their subsequently retrieved refractivity and dry temperature profiles, the quality of which is also degraded. The effects of the estimated background and observation error correlations on the atmospheric retrievals are investigated using simulated MetOp data. It is found that these realistically estimated correlations alone can reduce the random errors of the optimised bending angles significantly and improve the quality of the subsequent refractivities and temperatures. The performance of the new approach that uses only the new background matrix in the statistical optimisation on monthly occultation data is evaluated. The results show that the monthly errors are similar to those from single days, but in a smoother manner

A 20-YEAR CLIMATOLOGY OF GLOBAL ATMOSPHERIC METHANE FROM HYPERSPECTRAL THERMAL INFRARED SOUNDERS WITH SOME APPLICATIONS

Atmospheric Methane (CH4) is the second most important greenhouse gas after carbon dioxide (CO2), and accounts for approximately 20% of the global warming produced by all well-mixed greenhouse gases. Thus, its spatiotemporal distributions and relevant long-term trends are critical to understanding the sources, sinks, and global budget of atmospheric composition, as well as the associated climate impacts. The current suite of hyperspectral thermal infrared sounders has provided continuous global methane data records since 2002, starting with the Atmospheric Infrared Sounder (AIRS) onboard the NASA EOS/Aqua satellite launched on 2 May 2002. The Cross-track Infrared Sounder (CrIS) was launched onboard the Suomi National Polar Orbiting Partnership (SNPP) on 28 October 2011 and then on NOAA-20 on 18 November 2017. The Infrared Atmospheric Sounding Interferometer (IASI) was launched onboard the EUMETSAT MetOp-A on 19 October 2006, followed by MetOp-B on 17 September 2012, then Metop-C on 7 November 2018. In this study, nearly two decades of global CH4 concentrations retrieved from the AIRS and CrIS sensors were analyzed. Results indicate that the global mid-upper tropospheric CH4 concentrations (centered around 400 hPa) increased significantly from 2003 to 2020, i.e., with an annual average of ~1754 ppbv in 2003 and ~1839 ppbv in 2020. The total increase is approximately 85 ppbv representing a +4.8% change in 18 years. More importantly, the rate of increase was derived using satellite measurements and shown to be consistent with the rate of increase previously reported only from in-situ observational measurements. It further confirmed that there was a steady increase starting in 2007 that became stronger since 2014, as also reported from the in-situ observations. In addition, comparisons of the methane retrieved from the AIRS and CrIS against in situ measurements from NOAA Global Monitoring Laboratory (GML) were conducted. One of the key findings of this comparative study is that there are phase shifts in the seasonal cycles between satellite thermal infrared measurements and ground measurements, especially in the middle to high latitudes in the northern hemisphere. Through this, an issue common in the hyperspectral thermal sensor retrievals were discovered that was unknown previously and offered potential solutions. We also conducted research on some applications of the retrieval products in monitoring the changes of CH4 over the selected regions (the Arctic and South America). Detailed analyses based on local geographic changes related to CH4 concentration increases were discussed. The results of this study concluded that while the atmospheric CH4 concentration over the Arctic region has been increasing since the early 2000s, there were no catastrophic sudden jumps during the period of 2008-2012, as indicated by the earlier studies using pre-validated retrieval products. From our study of CH4 climatology using hyperspectral infrared sounders, it has been proved that the CH4 from hyperspectral sounders provide valuable information on CH4 for the mid-upper troposphere and lower stratosphere. Future approaches are suggested that include: 1) Utilizing extended data records for CH4 monitoring using AIRS, CrIS, and other potential new generation hyperspectral infrared sensors; 2). Improving the algorithms for trace gas retrievals; and 3). Enhancing the capacity to detect CH4 changes and anomalies with radiance signals from hyperspectral infrared sounders

Advances in Remote Sensing-based Disaster Monitoring and Assessment

Remote sensing data and techniques have been widely used for disaster monitoring and assessment. In particular, recent advances in sensor technologies and artificial intelligence-based modeling are very promising for disaster monitoring and readying responses aimed at reducing the damage caused by disasters. This book contains eleven scientific papers that have studied novel approaches applied to a range of natural disasters such as forest fire, urban land subsidence, flood, and tropical cyclones

Beyond 100: The Next Century in Geodesy

This open access book contains 30 peer-reviewed papers based on presentations at the 27th General Assembly of the International Union of Geodesy and Geophysics (IUGG). The meeting was held from July 8 to 18, 2019 in Montreal, Canada, with the theme being the celebration of the centennial of the establishment of the IUGG. The centennial was also a good opportunity to look forward to the next century, as reflected in the title of this volume. The papers in this volume represent a cross-section of present activity in geodesy, and highlight the future directions in the field as we begin the second century of the IUGG. During the meeting, the International Association of Geodesy (IAG) organized one Union Symposium, 6 IAG Symposia, 7 Joint Symposia with other associations, and 20 business meetings. In addition, IAG co-sponsored 8 Union Symposia and 15 Joint Symposia. In total, 3952 participants registered, 437 of them with IAG priority. In total, there were 234 symposia and 18 Workshops with 4580 presentations, of which 469 were in IAG-associated symposia. ; This volume will publish papers based on International Association of Geodesy (IAG) -related presentations made at the International Association of Geodesy at the 27th IUGG General Assembly, Montreal, July 2019. It will include papers associated with all of the IAG and joint symposia from the meeting, which span all aspects of modern geodesy, and linkages to earth and environmental sciences. It continues the long-running IAG Symposia Series

The Future of Remote Sensing From Space: Civilian Satellite Systems and Applications

This report examines issues related to the development and operation of publicly funded U.S. and foreign civilian remote sensing systems. It also explores the military and intelligence use of data gathered by civilian satellites. In addition, the report examines the outlook for privately funded and operated remote sensing systems

Beyond 100: The Next Century in Geodesy

This open access book contains 30 peer-reviewed papers based on presentations at the 27th General Assembly of the International Union of Geodesy and Geophysics (IUGG). The meeting was held from July 8 to 18, 2019 in Montreal, Canada, with the theme being the celebration of the centennial of the establishment of the IUGG. The centennial was also a good opportunity to look forward to the next century, as reflected in the title of this volume. The papers in this volume represent a cross-section of present activity in geodesy, and highlight the future directions in the field as we begin the second century of the IUGG. During the meeting, the International Association of Geodesy (IAG) organized one Union Symposium, 6 IAG Symposia, 7 Joint Symposia with other associations, and 20 business meetings. In addition, IAG co-sponsored 8 Union Symposia and 15 Joint Symposia. In total, 3952 participants registered, 437 of them with IAG priority. In total, there were 234 symposia and 18 Workshops with 4580 presentations, of which 469 were in IAG-associated symposia. ; This volume will publish papers based on International Association of Geodesy (IAG) -related presentations made at the International Association of Geodesy at the 27th IUGG General Assembly, Montreal, July 2019. It will include papers associated with all of the IAG and joint symposia from the meeting, which span all aspects of modern geodesy, and linkages to earth and environmental sciences. It continues the long-running IAG Symposia Series