Global Distributions, Time Series and Error Characterization of Atmospheric Ammonia
ثبت نشده
چکیده
Ammonia (NH3) emissions in the atmosphere have increased substantially over the past decades, largely because of intensive livestock production and use of fertilizers. As a short-lived species, NH3 is highly variable in the atmosphere and its concentration is generally small, except near local sources. While ground-based measurements are possible, they are challenging and sparse. Advanced infrared sounders in orbit have recently demonstrated their capability to measure NH3, offering a new tool to refine global and regional budgets. In this paper we describe an improved retrieval scheme of NH3 total columns from the measurements of the Infrared Atmospheric Sounding Interferometer (IASI). It exploits the hyperspectral character of this instrument by using an extended spectral range (800–1200 cm−1) where NH3 is optically active. This scheme consists of the calculation of a dimensionless spectral index from the IASI level1C radiances, which is subsequently converted to a total NH3 column using look-up tables built from forward radiative transfer model simulations. We show how to retrieve the NH3 total columns from IASI quasi-globally and twice daily above both land and sea without large computational resources and with an improved detection limit. The retrieval also includes error characterization of the retrieved columns. Five years of IASI measurements (1 November 2007 to 31 October 2012) have been processed to acquire the first global and multiple-year data set of NH3 total columns, which are evaluated and compared to similar products from other retrieval methods. Spatial distributions from the five years data set are provided and analyzed at global and regional scales. In particular, we show the ability of this method to identify smaller emission sources than those previously reported, as well as transport patterns over the ocean. The five-year time series is further examined in terms of seasonality and inter-annual variability (in particular as a function of fire activity) separately for the Northern and Southern Hemispheres.
منابع مشابه
Global distributions, time series and error characterization of atmospheric ammonia (NH[subscript 3]) from IASI satellite observations
Ammonia (NH3) emissions in the atmosphere have increased substantially over the past decades, largely because of intensive livestock production and use of fertilizers. As a short-lived species, NH3 is highly variable in the atmosphere and its concentration is generally small, except near local sources. While ground-based measurements are possible, they are challenging and sparse. Advanced infra...
متن کاملStatistical modeling of the association between pervasive precipitation anomalies in Southern Alburz and global ocean-atmospheric patterns
Precipitation patterns are influenced by many factors, such as global atmospheric circulations to name but one. Precipitation patterns in Iran have always had great fluctuations even in a smaller scale like the Alburz Mountain Range. The present research has tried to find the relationship between global atmospheric patterns and the pervasive precipitation ones in Alburz. For doing so, 17 climat...
متن کاملStatistical modeling of the association between pervasive precipitation anomalies in Southern Alburz and global ocean-atmospheric patterns
Precipitation patterns are influenced by many factors, such as global atmospheric circulations to name but one. Precipitation patterns in Iran have always had great fluctuations even in a smaller scale like the Alburz Mountain Range. The present research has tried to find the relationship between global atmospheric patterns and the pervasive precipitation ones in Alburz. For doing so, 17 climat...
متن کاملMitigation of Tropospheric Delay on InSAR Interseismic Displacements
One of the major challenges of Interferometric Synthetic Aperture Radar (InSAR) technique is the existence of tropospheric effect on the results. The tropospheric effect is due to the changes of atmospheric parameters including temperature, pressure, and humidity between the master and slave images. In this research, two different methods based on spatial-temporal filters and calculation of pha...
متن کاملApplication of ensemble learning techniques to model the atmospheric concentration of SO2
In view of pollution prediction modeling, the study adopts homogenous (random forest, bagging, and additive regression) and heterogeneous (voting) ensemble classifiers to predict the atmospheric concentration of Sulphur dioxide. For model validation, results were compared against widely known single base classifiers such as support vector machine, multilayer perceptron, linear regression and re...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2015