[1] In this paper CMOD5, a new C-band geophysical model function (GMF), is derived on the basis of measurements from the scatterometer on board of the European Remote Sensing Satellite ERS-2. First-guess winds from the European Centre for Medium-Range Weather Forecasts were used as a reference for the period from August to December 1998, adding up to more than 22,000,000 collocations. CMOD5 corrects some deficiencies of the currently widely used CMOD4 GMF. Linear and higher-order wind speed corrections as computed with a triple collocation method are implemented. Recent measurements of extreme backscatter and wind obtained by aircraft and in situ data are fitted. Also, a more accurate fit of the two-dimensional cone surface in threedimensional measurement space is established, especially in the regime of strong winds. These improvements result not only in better wind retrievals at high wind speed, but also in a more uniform performance across the ERS scatterometer swath. Moreover, the wind ambiguity problem has been reduced owing to the improved fit of the cone surface, resulting in about 75% skill of the first rank solution for winds above 10 m/s. These improvements aid the general usefulness of retrieved C-band scatterometer winds for climate and weather applications, and the ambiguity removal in dynamical and extreme weather conditions in particular.
Abstract. Global navigation satellite systems (GNSSs) have revolutionised positioning, navigation, and timing, becoming a common part of our everyday life. Aside from these well-known civilian and commercial applications, GNSS is now an established atmospheric observing system, which can accurately sense water vapour, the most abundant greenhouse gas, accounting for 60-70 % of atmospheric warming. In Europe, the application of GNSS in meteorology started roughly two decades ago, and today it is a well-established field in both research and operation. This review covers the state of the art in GNSS meteorology in Europe. The advances in GNSS processing for derivation of tropospheric products, application of GNSS tropospheric products in operational weather prediction and application of GNSS tropospheric products for climate monitoring are discussed. The GNSS processing techniques and tropospheric products are reviewed. A summary of the use of the products for validation and impact studies with operational numerical weather prediction (NWP) models as well as very short weather prediction (nowcasting) case studies is given. Climate research with GNSSs is an emerging field of research, but the studies so far have been limited to comparison with climate models and derivation of trends.More than 15 years of GNSS meteorology in Europe has already achieved outstanding cooperation between the atmospheric and geodetic communities. It is now feasible to develop next-generation GNSS tropospheric products and applications that can enhance the quality of weather forecasts and climate monitoring. This work is carried out within COST Action ES1206 advanced global navigation satellite systems tropospheric products for monitoring severe weather events and climate (GNSS4SWEC, http://gnss4swec.knmi. nl).
[1] Wind, temperature, and humidity observations from radiosonde and aircraft are the main sources of upper air information for meteorology. For mesoscale meteorology, the horizontal coverage of radiosondes is too sparse. Aircraft observations through Aircraft Meteorological Data Relay (AMDAR) sample an atmospheric profile in the vicinity of airports. However, not all aircraft are equipped with AMDAR or have the system activated. Observations inferred from an enhanced tracking and ranging (TAR) air traffic control radar can fill this gap. These radars follows all aircraft in the airspace visible to the radar for air traffic management. The TAR radar at Schiphol airport in Netherlands has a range of 270 km. This Mode-S radar contacts each aircraft every 4 s on which the transponder in the aircraft responds with a message that contains information on flight level, direction, and speed. Combined with the ground track of an aircraft, meteorological information on temperature and wind can be inferred from this information. Because all aircraft are required to respond to the TAR radar, the data volume is extremely large, being around 1.5 million observations per day. Note that there are no extra costs for this data link. The quality of these observations is assessed by comparison to numerical weather prediction (NWP) model information, AMDAR observations, and radiosonde observations. A preprocessing step is applied to enhance the quality of wind and temperature observations, albeit with a reduced time frequency of one observation of horizontal wind vector and temperature per aircraft per minute. Nevertheless, the number of observations per day is still very large. In this paper it is shown that temperature observations from Mode-S, even after corrections, are not very good; an RMS which is twice as large as AMDAR is observed when compared to NWP. In contrast to the temperature observations, the quality found for wind after correction and calibration is good; it is comparable to AMDAR, slightly worse than radiosonde but certainly very valuable for mesoscale NWP.
SUMMARYWithin the Atmospheric Dynamics Mission Aeolus (ADM-Aeolus), the European Space Agency (ESA) has approved a Doppler wind lidar (DWL) to fly on a dedicated platform orbiting dawn to dusk at 400 km altitude, planned for launch in 2008. Rigorous design trade-offs have resulted in a lidar concept capable of delivering high-quality wind component profiles, but with a limited coverage. A companion paper describes the realistic simulation of this DWL, whereas this paper sets out to assess the impact of such a lidar in meteorological analyses and forecasts. To this end, an Observing System Simulation Experiment (OSSE) is run. The superior conventional observation coverage of 1993 is used to simulate all conventional observations, although a limited set of satellite observations is simulated. As a consequence, only the northern hemisphere DWL impact in the OSSE is assumed realistic. Here, over a 15-day period with variable weather, out of 15 daily forecasts, 14 show beneficial impact of the DWL. Although the experiment is limited, it corroborates other practical and theoretical evidence that the ADM DWL will demonstrate a beneficial impact in meteorological analyses and forecasts.
In this paper the beneficial impacts of high-resolution (in space and time) wind and temperature observations from aircraft on very short-range numerical weather forecasting are presented. The observations are retrieved using the tracking and ranging radar from the air traffic control facility at Schiphol Airport, Amsterdam, the Netherlands. This enhanced surveillance radar tracks all aircraft in sight every 4 s, generating one million wind and temperature observations per day in a radius of 270 km around the radar. Nowcasting applications will benefit from improved three-dimensional wind fields. When these observations are assimilated into a numerical model with an hourly update cycle, the short-range three-dimensional wind field forecasts match the observations better than those from an operational forecast cycle, which is updated every 3 h. The positive impact on wind in the first hours of the forecast gradually turns into a neutral impact, when compared to other wind and temperature observations. The timeliness of the forecasts combined with the high resolution of the observations are the main reasons for the observed nowcasting benefits. All in all, the assimilation of high-resolution wind (and temperature) observations is found to be beneficial for nowcasting and short-range forecasts up to 2-3 h.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.