Carlos Jiménez

Validation of the Aura Microwave Limb Sounder middle atmosphere water vapor and nitrous oxide measurements

[1] The quality of the version 2.2 (v2.2) middle atmosphere water vapor and nitrous oxide measurements from the Microwave Limb Sounder (MLS) on the Earth Observing System (EOS) Aura satellite is assessed. The impacts of the various sources of systematic error are estimated by a comprehensive set of retrieval simulations. Comparisons with correlative data sets from ground-based, balloon and satellite platforms operating in the UV/visible, infrared and microwave regions of the spectrum are performed. Precision estimates are also validated, and recommendations are given on the data usage. The v2.2 H2O data have been improved over v1.5 by providing higher vertical resolution in the lower stratosphere and better precision above the stratopause. The single-profile precision is � 0.2–0.3 ppmv (4–9%), and the vertical resolution is � 3–4 km in the stratosphere. The precision and vertical resolution become worse with increasing height above the stratopause. Over the pressure range 0.1–0.01 hPa the precision degrades from 0.4 to 1.1 ppmv (6–34%), and the vertical resolution degrades to � 12–16 km. The accuracy is estimated to be 0.2–0.5 ppmv (4–11%) for the pressure range 68–0.01 hPa. The scientifically useful range of the H2O data is from 316 to 0.002 hPa, although only the 82–0.002 hPa pressure range is validated here. Substantial improvement has been achieved in the v2.2 N2O data over v1.5 by reducing a significant low bias in the stratosphere and eliminating unrealistically high biased mixing ratios in the polar regions. The single-profile precision is � 13–25 ppbv (7–38%), the vertical resolution is � 4–6 km and the accuracy is estimated to be 3–70 ppbv (9–25%) for the pressure range 100–4.6 hPa. The scientifically useful range of the N2O data is from 100 to 1 hPa.

Odin/SMR limb observations of stratospheric trace gases: Level 2 processing of ClO, N2O, HNO3, and O3

The Sub-Millimetre Radiometer (SMR) on board the Odin satellite, launched on 20 February 2001, observes key species with respect to stratospheric chemistry and dynamics such as O-3, ClO, N2O, and HNO3 using two bands centered at 501.8 and 544.6 GHz. We present the adopted methodology for level 2 processing and the achieved in-orbit measurement capabilities of the SMR radiometer for these species in terms of altitude range, altitude resolution, and measurement precision. The characteristics of the relevant level 2 data versions, namely version 1.2 of the operational processor as well as versions 222 and 223 of the reference code, are discussed and differences are evaluated. An analysis of systematic retrieval errors, resulting from spectroscopic and instrumental uncertainties, is also presented.

Soil Moisture Retrieval Using Neural Networks: Application to SMOS

A methodology to retrieve soil moisture (SM) from Soil Moisture and Ocean Salinity (SMOS) data is presented. The method uses a neural network (NN) to find the statistical relationship linking the input data to a reference SM data set. The input data are composed of passive microwaves (L-band SMOS brightness temperatures,

Odin/SMR limb observations of stratospheric trace gases: Validation of N2O

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Strato‐mesospheric measurements of carbon monoxide with the Odin Sub‐Millimetre Radiometer: Retrieval and first results

s) complemented with active microwaves (C-band Advanced Scatterometer (ASCAT) backscattering coefficients), and Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) . The reference SM data used to train the NN are the European Centre For Medium-Range Weather Forecasts model predictions. The best configuration of SMOS data to retrieve SM using an NN is using

A Hotelling transformation approach for rapid inversion of atmospheric spectra

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Multiangle Backscattering Observations of Continental Surfaces in Ku-Band (13 GHz) From Satellites: Understanding the Signals, Particularly in Arid Regions

s measured with both H and V polarizations for incidence angles from 25° to 60°. The inversion of SM can be improved by ~10% by adding MODIS NDVI and ASCAT backscattering data and by an additional ~5% by using local information on the maximum and minimum records of SMOS Tbs (or ASCAT backscattering coefficients) and the associated SM values. The NN-inverted SM is able to capture the temporal and spatial variability of the SM reference data set. The temporal variability is better captured when either adding active microwaves or using a local normalization of SMOS Tbs. The NN SM products have been evaluated against in situ measurements, giving results of comparable or better (for some NN configurations) quality to other SM products. The NN used in this paper allows to retrieve SM globally on a daily basis. These results open interesting perspectives such as a near-real-time processor and data assimilation in weather prediction models.

Soil moisture retrieval from SMOS observations using neural networks

The Sub-Millimetre Radiometer (Odin/SMR) on board the Odin satellite, launched on 20 February 2001, performs regular measurements of the global distribution of stratospheric nitrous oxide (N2O) using spectral observations of the J = 20R 19 rotational transition centered at 502.296 GHz. We present a quality assessment for the retrieved N2O profiles (level 2 product) by comparison with independent balloonborne and aircraftborne validation measurements as well as by cross-comparing with preliminary results from other satellite instruments. An agreement with the airborne validation experiments within 28 ppbv in terms of the root mean square (RMS) deviation is found for all SMR data versions (v222, v223, and v1.2) under investigation. More precisely, the agreement is within 19 ppbv for N2O volume mixing ratios (VMR) lower than 200 ppbv and within 10% for mixing ratios larger than 150 ppbv. Given the uncertainties due to atmospheric variability inherent to such comparisons, these values should be interpreted as upper limits for the systematic error of the Odin/SMR N2O measurements. Odin/SMR N2O mixing ratios are systematically slightly higher than nonvalidated data obtained from the Improved Limb Atmospheric Spectrometer-II (ILAS-II) on board the Advanced Earth Observing Satellite-II (ADEOS-II). Root mean square deviations are generally within 23 ppbv (or 20% for VMR-N2O > 100 ppbv) for versions 222 and 223. The comparison with data obtained from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on the Envisat satellite yields a good agreement within 9-17 ppbv (or 10% for VMR-N2O > 100 ppbv) for the same data versions. Odin/SMR version 1.2 data show somewhat larger RMS deviations and a higher positive bias.

A neural network technique for inversion of atmospheric observations from microwave limb sounders

The Sub-Millimetre Radiometer (SMR) aboard the Odin satellite has been measuring vertical profiles of atmospheric trace gases since August 2001. We present the inversion methodology developed for CO measurements and the first retrieval results. CO can be retrieved from a single scan measurement throughout the middle atmosphere, with a typical resolution of similar to3 km and a relative error of similar to10% to similar to25%. Retrieval results are evaluated through comparison with data from the Whole Atmosphere Community Climate Model (WACCM) and observations of the Improved Stratospheric and Mesospheric Sounder (ISAMS) on board the Upper Atmospheric Research Satellite (UARS). Considering the large natural variability of CO, the SMR retrievals give good confirmation of the WACCM results, with an overall agreement within a factor of 2. ISAMS abundances are higher than SMR mixing ratios by a factor of 5-10 above 0.5 hPa from similar to80degreesS to similar to50degreesN.

Sources of discrepancies between satellite‐derived and land surface model estimates of latent heat fluxes

Atmospheric observations from space often result in spectral data of large dimensions. To allow an optimal inversion of the observed spectra it can be necessary to map the data into a space of smaller dimension. Here several data reduction techniques based on eigenvector expansions of the spectral space are compared. The comparison is done by inverting simulated observations from a microwave limb sounder, the Odin-SMR. For the examples tested, reductions exceeding two orders of magnitude with no negative influence on the retrieval performance are demonstrated. The techniques compared include a novel method developed especially for atmospheric inversions, based on the weighting functions of the variables to be retrieved. The new method shows an excellent performance in practical tests and is both computationally more effective and more flexible than the standard Hotelling transformation.