Deep convective clouds at the tropopause

Data from the Atmospheric Infrared Sounder (AIRS) on the EOS Aqua spacecraft each day show tens of thousands of Cold Clouds (CC) in the tropical oceans with 10 μm window channel brightness temperatures colder than 225 K. These clouds represent a mix of cold anvil clouds and Deep Convective Clouds (DCC). This mix can be separated by computing the difference between two channels, a window channel and a channel with strong CO<sub>2</sub> absorption: for some cold clouds this difference is negative, i.e. the spectra for some cold clouds are inverted. We refer to cold clouds with spectra which are more than 2 K inverted as DCCi2. Associated with DCCi2 is a very high rain rate and a local upward displacement of the tropopause, a cold "bulge", which can be seen directly in the brightness temperatures of AIRS and Advanced Microwave Sounding Unit (AMSU) temperature sounding channels in the lower stratosphere. The very high rain rate and the local distortion of the tropopause indicate that DCCi2 objects are associated with severe storms. Significant long-term trends in the statistical properties of DCCi2 could be interesting indicators of climate change. While the analysis of the nature and physical conditions related to DCCi2 requires hyperspectral infrared and microwave data, the identification of DCCi2 requires only one good window channel and one strong CO<sub>2</sub> sounding channel. This suggests that improved identification of severe storms with future advanced geostationary satellites could be accomplished with the addition of one or two narrow band channels

Horizontal small-scale variability of water vapor in the atmosphere: implications for intercomparison of data from different measuring systems

Water vapor concentration structures in the atmosphere are well approximated horizontally by Gaussian random fields at small scales (≲6 km). These Gaussian random fields have a spatial correlation in accordance with a structure function with a two-thirds slope, following the corresponding law from Kolmogorov's theory of turbulence. This is proven by showing that the horizontal structure functions measured by several satellite instruments and radiosonde measurements do indeed follow the two-thirds law. High-spatial-resolution retrievals of total column water vapor (TCWV) obtained from the Ocean and Land Color Instrument (OLCI) on board the Sentinel-3 series of satellites also qualitatively show a Gaussian random field structure. As a consequence, the atmosphere has an inherently stochastic component associated with the horizontal small-scale water vapor features, which, in turn, can make deterministic forecasting or nowcasting difficult. These results can be useful in areas where high-resolution modeling of water vapor is required, such as the estimation of the water vapor variance within a region or when searching for consistency between different water vapor measurements in neighboring locations. In terms of weather forecasting or nowcasting, the water vapor horizontal variability could be important in estimating the uncertainty of the atmospheric processes driving convection.</p

Sheared Flow As A Stabilizing Mechanism In Astrophysical Jets

It has been hypothesized that the sustained narrowness observed in the asymptotic cylindrical region of bipolar outflows from Young Stellar Objects (YSO) indicates that these jets are magnetically collimated. The j cross B force observed in z-pinch plasmas is a possible explanation for these observations. However, z-pinch plasmas are subject to current driven instabilities (CDI). The interest in using z-pinches for controlled nuclear fusion has lead to an extensive theory of the stability of magnetically confined plasmas. Analytical, numerical, and experimental evidence from this field suggest that sheared flow in magnetized plasmas can reduce the growth rates of the sausage and kink instabilities. Here we propose the hypothesis that sheared helical flow can exert a similar stabilizing influence on CDI in YSO jets.Comment: 13 pages, 2 figure

Intercomparison of desert dust optical depth from satellite measurements

This work provides a comparison of satellite retrievalsof Saharan desert dust aerosol optical depth (AOD)during a strong dust event through March 2006. In this event,a large dust plume was transported over desert, vegetated,and ocean surfaces. The aim is to identify the differencesbetween current datasets. The satellite instruments consideredare AATSR, AIRS, MERIS, MISR, MODIS, OMI,POLDER, and SEVIRI. An interesting aspect is that the differentalgorithms make use of different instrument characteristicsto obtain retrievals over bright surfaces. These includemulti-angle approaches (MISR, AATSR), polarisationmeasurements (POLDER), single-view approaches using solarwavelengths (OMI, MODIS), and the thermal infraredspectral region (SEVIRI, AIRS). Differences between instruments,together with the comparison of different retrievalalgorithms applied to measurements from the same instrument,provide a unique insight into the performance andcharacteristics of the various techniques employed. As wellas the intercomparison between different satellite products,the AODs have also been compared to co-located AERONETdata. Despite the fact that the agreement between satellite andAERONET AODs is reasonably good for all of the datasets,there are significant differences between them when comparedto each other, especially over land. These differencesare partially due to differences in the algorithms, such as assumptionsabout aerosol model and surface properties. However,in this comparison of spatially and temporally averageddata, it is important to note that differences in sampling, relatedto the actual footprint of each instrument on the heterogeneousaerosol field, cloud identification and the qualitycontrol flags of each dataset can be an important issue

Pressure-driven instabilities in astrophysical jets

Astrophysical jets are widely believed to be self-collimated by the hoop-stress due to the azimuthal component of their magnetic field. However this implies that the magnetic field is largely dominated by its azimuthal component in the outer jet region. In the fusion context, it is well-known that such configurations are highly unstable in static columns, leading to plasma disruption. It has long been pointed out that a similar outcome may follow for MHD jets, and the reasons preventing disruption are still not elucidated, although some progress has been accomplished in the recent years. In these notes, I review the present status of this open problem for pressure-driven instabilities, one of the two major sources of ideal MHD instability in static columns (the other one being current-driven instabilities). I first discuss in a heuristic way the origin of these instabilities. Magnetic resonances and magnetic shear are introduced, and their role in pressure-driven instabilities discussed in relation to Suydam's criterion. A dispersion relation is derived for pressure-driven modes in the limit of large azimuthal magnetic fields, which gives back the two criteria derived by Kadomtsev for this instability. The growth rates of these instabilities are expected to be short in comparison with the jet propagation time. What is known about the potential stabilizing role of the axial velocity of jets is then reviewed. In particular, a nonlinear stabilization mechanism recently identified in the fusion literature is discussed. Key words: Ideal MHD: stability, pressure-driven modes; Jets: stabilityComment: 20 pages, 3 figures. Lecture given at the JETSET European school "Numerical MHD and Instabilities". To be published by Springer in the "Lectures notes in physics" serie

Improving the Understanding of CrIS Full Spectral Resolution Nonlocal Thermodynamic Equilibrium Radiances Using Spectral Correlation

In recent years, significant progress has been made in fast radiative transfer model (RTM) simulation of daytime nonlocal thermodynamic equilibrium (NLTE) emission. However, NLTE remains as one important reason that prevents the hyperspectral shortwave infrared (SWIR) radiance observations from being assimilated into numerical weather prediction (NWP) models. To better understand the limitations of existing RTM-based NLTE simulation, this study introduces a new statistical method, called Spectral Correlations to Estimate Non-Local Thermal Equilibrium (SCENTE), to estimate the NLTE radiances in the Cross-track Infrared Sounder (CrIS) SWIR radiance observations. SCENTE is applied to four typical season days, including spring equinox, summer solstice, fall equinox, and winter solstice. By analyzing calculation/background minus observation (BMO) of CrIS SWIR brightness temperature (BT), results show that SCENTE characterizes the NLTE well with standard deviation of differences (STD) comparable to observation noise for both daytime and nighttime, while the community RTM (CRTM) has substantially larger STD at night, mainly due to the lack of daytime NLTE just beyond the day/night terminator and the lack of aurora-related NLTE. Detailed investigation of the biases of BMO shows that CRTM underestimates daytime SWIR NLTE effects by 0.76 K, while SCENTE overestimates SWIR NLTE effects by 0.70 K. The overestimation is because SCENTE uses CRTM-simulated SWIR local thermodynamic equilibrium (LTE) radiances in the training, which is underestimated by 0.70 K in BT. SCENTE, complementary to RTM-based simulations, can be used for quality control of SWIR radiances for assimilation and retrieval of atmospheric soundings. ©2020. American Geophysical Union. All Rights ReservedThis work is supported by CIMSS internal funding and GOES‐R and JPSS science projects at CIMSS of the National Oceanic and Atmospheric Administration (NA15NES4320001). The views, opinions, and findings contained in this report are those of the authors and should not be construed as an official National Oceanic and Atmospheric Administration's or U.S. Government's position, policy, or decision. The authors thank Dr. Christopher D. Barnet, Dr. Di Di, and Dr. Wenguang Bai for their valuable discussion, comments, and suggestions on this work and the three anonymous reviewers for their very useful comments to improve our paper. Timothy J. Schmit of NOAA NESDIS is thanked for a review of the manuscript. Manuel López‐Puertas was supported by the Spanish Ministerio de Ciencia, Innovación y Universidades (MICINN) under Project ESP2017‐87143‐R and EC FEDER (European Regional Development Fund) funds.Peer reviewe

Single-footprint retrievals for AIRS using a fast TwoSlab cloud-representation model and the SARTA all-sky infrared radiative transfer algorithm

One-dimensional variational retrievals of temperature and moisture fields from hyperspectral infrared (IR) satellite sounders use cloud-cleared radiances (CCRs) as their observation. These derived observations allow the use of clear-sky-only radiative transfer in the inversion for geophysical variables but at reduced spatial resolution compared to the native sounder observations. Cloud clearing can introduce various errors, although scenes with large errors can be identified and ignored. Information content studies show that, when using multilayer cloud liquid and ice profiles in infrared hyperspectral radiative transfer codes, there are typically only 2–4 degrees of freedom (DOFs) of cloud signal. This implies a simplified cloud representation is sufficient for some applications which need accurate radiative transfer. Here we describe a single-footprint retrieval approach for clear and cloudy conditions, which uses the thermodynamic and cloud fields from numerical weather prediction (NWP) models as a first guess, together with a simple cloud-representation model coupled to a fast scattering radiative transfer algorithm (RTA). The NWP model thermodynamic and cloud profiles are first co-located to the observations, after which the N-level cloud profiles are converted to two slab clouds (TwoSlab; typically one for ice and one for water clouds). From these, one run of our fast cloud-representation model allows an improvement of the a priori cloud state by comparing the observed and model-simulated radiances in the thermal window channels. The retrieval yield is over 90 %, while the degrees of freedom correlate with the observed window channel brightness temperature (BT) which itself depends on the cloud optical depth. The cloud-representation and scattering package is benchmarked against radiances computed using a maximum random overlap (RMO) cloud scheme. All-sky infrared radiances measured by NASA's Atmospheric Infrared Sounder (AIRS) and NWP thermodynamic and cloud profiles from the European Centre for Medium-Range Weather Forecasts (ECMWF) forecast model are used in this paper

Can turbulence within the field of view cause significant biases in radiative transfer modeling at the 183&thinsp;GHz band?

The hypothesis whether turbulence within the passive microwave sounders field of view can cause significant biases in radiative transfer modeling at the 183&thinsp;GHz water vapor absorption band is tested. A novel method to calculate the effects of turbulence in radiative transfer modeling is presented. It is shown that the turbulent nature of water vapor in the atmosphere can be a critical component of radiative transfer modeling in this band. Radiative transfer simulations are performed comparing a uniform field with a turbulent one. These comparisons show frequency dependent biases which can be up to several kelvin in brightness temperature. These biases can match experimentally observed biases, such as the ones reported in Brogniez et al. (2016). Our simulations show that those biases could be explained as an effect of high-intensity turbulence in the upper troposphere. These high turbulence phenomena are common in clear air turbulence, storm or cumulus cloud situations.</p