THz spectroscopy of the atmosphere for climatology and meteorology applications

We present a new satellite-based instrument concept that will enable global measurements of atmospheric temperature and humidity profiles with unprecedented resolution and accuracy, compared to currently planned missions. It will also provide global measurements of essential climate variables related to ice clouds that will better constrain global climate models. The instrument is enabled by the use of superconducting detectors coupled to superconducting filterbank spectrometers, operating between 50GHz and 850 GHz. We present the science drivers, the current instrument concept and status, and predicted performance

A 1D RCE study of factors affecting the tropical tropopause layer and surface climate

There are discrepancies between global climate models regarding the evolution of the tropical tropopause layer (TTL) and also whether changes in ozone impact the surface under climate change. We use a 1D clear-sky radiative–convective equilibrium model to determine how a variety of factors can affect the TTL and how they influence surface climate. We develop a new method of convective adjustment, which relaxes the temperature profile toward the moist adiabat and allows for cooling above the level of neutral buoyancy. The TTL temperatures in our model are sensitive to CO2 concentration, ozone profile, the method of convective adjustment, and the upwelling velocity, which is used to calculate a dynamical cooling rate in the stratosphere. Moreover, the temperature response of the TTL to changes in each of the above factors sometimes depends on the others. The surface temperature response to changes in ozone and upwelling at and above the TTL is also strongly amplified by both stratospheric and tropospheric water vapor changes. With all these influencing factors, it is not surprising that global models disagree with regard to TTL structure and evolution and the influence of ozone changes on surface temperatures. On the other hand, the effect of doubling CO2 on the surface, including just radiative, water vapor, and lapse-rate feedbacks, is relatively robust to changes in convection, upwelling, or the applied ozone profile

All-sky information content analysis for novel passive microwave instruments in the range from 23.8 to 874.4 GHz

We perform an all-sky information content analysis for channels in the millimetre and sub-millimetre wavelength with 24 channels in the region from 23.8 to 874.4 GHz. The employed set of channels corresponds to the instruments ISMAR and MARSS, which are available on the British FAAM research aircraft, and it is complemented by two precipitation channels at low frequencies from Deimos. The channels also cover ICI, which will be part of the MetOp-SG mission. We use simulated atmospheres from the ICON model as basis for the study and quantify the information content with the reduction of degrees of freedom (Delta DOF). The required Jacobians are calculated with the radiative transfer model ARTS. Specifically we focus on the dependence of the information content on the atmospheric composition. In general we find a high information content for the frozen hydrometeors, which mainly comes from the higher frequency channels beyond 183.31 GHz (on average 3.10 for cloud ice and 2.57 for snow). Considerable information about the microphysical properties, especially for cloud ice, can be gained. The information content about the liquid hydrometeors comes from the lower frequency channels. It is 1.69 for liquid cloud water and 1.08 for rain using the full set of channels. The Jacobians for a specific cloud hydrometeor strongly depend on the atmospheric composition. Especially for the liquid hydrometeors the Jacobians even change sign in some cases. However, the information content is robust across different atmospheric compositions. For liquid hydrometeors the information content decreases in the presence of any frozen hydrometeor, for the frozen hydrometeors it decreases slightly in the presence of the respective other frozen hydrometeor. Due to the lack of channels below 183 GHz liquid hydrometeors are hardly seen by ICI. However, the overall results with regard to the frozen hydrometeors also hold for the ICI sensor. This points to ICI\u27s great ability to observe ice clouds from space on a global scale with a good spatial coverage in unprecedented detail

Dependence of Climate Sensitivity on the Given Distribution of Relative Humidity

International audienc

Effect of Uncertainty in Water Vapor Continuum Absorption on CO2 Forcing, Longwave Feedback, and Climate Sensitivity

Abstract We investigate the effect of uncertainty in water vapor continuum absorption at terrestrial wavenumbers on CO2 forcing F, longwave feedback λ, and climate sensitivity S at surface temperatures Ts between 270 and 330 K. We calculate this uncertainty using a line‐by‐line radiative‐transfer model and a single‐column atmospheric model, assuming a moist‐adiabatic temperature lapse‐rate and 80% relative humidity in the troposphere, an isothermal stratosphere, and clear skies. Due to the lack of a comprehensive model of continuum uncertainty, we represent continuum uncertainty in two different idealized approaches: In the first, we assume that the total continuum absorption is constrained at reference conditions; in the second, we assume that the total continuum absorption is constrained for all atmospheres in our model. In both approaches, we decrease the self continuum by 10% and adjust the foreign continuum accordingly. We find that continuum uncertainty mainly affects S through its effect on λ. In the first approach, continuum uncertainty mainly affects λ through a decrease in the total continuum absorption with Ts; in the second approach, continuum uncertainty affects λ through a vertical redistribution of continuum absorption. In both experiments, the effect of continuum uncertainty on S is modest at Ts = 288 K (≈0.02 K) but substantial at Ts ≥ 300 K (up to 0.2 K), because at high Ts, the effects of decreasing the self continuum and increasing the foreign continuum have the same sign. These results highlight the importance of a correct partitioning between self and foreign continuum to accurately determine the temperature dependence of Earth's climate sensitivity

Git Patches to modify konrad to support scaling of absorption species in line-by-line calculations

<p>This file includes the git patches that need to be applied to konrad version 1.0.1 (https://zenodo.org/record/6046423) to support the scaling of absorption species in the radiation interface with the line-by-line model ARTS. To this end, ARTS needs to be run on-the-fly (i.e., without an absorption lookup table).</p>This work was financially supported by the US National Science Foundation (award AGS-1916908) and by NOAA (award NA20OAR4310375)

Git Patches to modify konrad to support scaling of absorption species in line-by-line calculations

<p>This file includes the git patches that need to be applied to konrad version 1.0.1 (https://zenodo.org/record/6046423) to support the scaling of absorption species in the radiation interface with the line-by-line model ARTS. To this end, ARTS needs to be run on-the-fly (i.e., without an absorption lookup table).</p>This work was financially supported by the US National Science Foundation (award AGS-1916908) and by NOAA (award NA20OAR4310375)

Supplementary code for "Effect of Uncertainty in Water Vapor Continuum Absorption on CO2 Forcing, Longwave Feedback, and Climate Sensitivity"

<h3>This directory contains the code needed to reproduce the findings and figures of "Effect of Uncertainty in Water Vapor Continuum Absorption on CO2 Forcing, Longwave Feedback, and Climate Sensitivity".</h3><p> </p><h4>To reproduce the data published with the manuscript:</h4><h4>spectral_olr.nc:</h4><ul><li>unzip modified_continuum_input_files.zip in the folder arts-cat-data/model/mt_ckd_4.0/</li><li>calculate spectral OLR using konrad and ARTS for different experiments (run_konrad_continuum.py). The variables are the continuum input file, and surface temperature to calculate the spectral longwave feedback, as well as perturbations of the surface temperature (+/- 1K) to calculate the surface/atmospheric feedback, and of the CO2 concentration (doubling) to calculate the radiative forcing.</li><li>reformat and save data (convert_data.py)</li></ul><h4>opacity_emission_level.nc:</h4><ul><li>calculate the optical depth of each vertical layer and each considered absorption species for different surface temperatures (calc_optical_depth.py)</li><li>vertically integrate optical depth (integrate_optical_depth.py)</li><li>calculate the emission level for each temperature (calc_emission_level.py)</li><li>merge the emission levels into one array (merge_emission_level.py)</li><li>reformat and save data (convert_data.py)</li></ul><h4>continuum_ref_abs_coef.nc</h4><ul><li>calculate absorption coefficient (proportional to optical depth) for reference conditions and save them (calc_abs_coef.py)</li><li>reformat and save data (convert_data.py)</li></ul><h4>modified_continuum_input_files.zip</h4><ul><li>read original data on self and foreign continuum from MT_CKD 4.0 and scale them (rescale_continuum.py)</li><li>the modified continuum files have to be located in the folder arts-cat-data/model/mt_ckd_4.0/ to run run_konrad_continuum.py</li></ul><h4> </h4><h4>To reproduce the figures:</h4><h4>Figure 1 & 2:</h4><ul><li>calculate the absorption cross-section of the self continuum (calc_cross_section.py)</li><li>plot opacity and cross sections (plot_Fig1_Fig2.py)</li></ul><h4>Figure 3 & 4:</h4><ul><li>calculate spectrally resolved and integrated feedbacks, forcing and plot them (plot_Fig3_4.py)</li></ul><h4>Figure 5:</h4><ul><li>calculate emission fraction (calc_emission_fraction.py)</li><li>read opacity, emission fraction, spectral OLR, and spectral feedbacks and plot them (plot_Fig5.py)</li></ul><h4>Figure 6:</h4><ul><li>calculate absorption coefficient (proportional to optical depth) for reference conditions and save them (calc_abs_coef.py)</li><li>read absorption coefficients, calculate scaling factors and plot them (plot_Fig6.py)</li></ul><p>This work was financially supported by the US National Science Foundation (award AGS-1916908) and by NOAA (award NA20OAR4310375).</p&gt

Supplementary data for "Effect of Uncertainty in Water Vapor Continuum Absorption on CO2 Forcing, Longwave Feedback, and Climate Sensitivity"

<p>This dataset contains the spectral outgoing longwave radiation (OLR) calculated using the line-by-line radiative transfer model ARTS and the radiative-convective equilibrium model konrad. It contains spectral OLR for surface temperatures from 270K to 330K for different strengths of the water vapor continuum absorption (spectral_olr.nc).</p> <p>The dataset also contains the spectrally resolved optical depth and the emission level of outgoing longwave radiation for the considered absorption species (H2O lines, H2O continuum, H2O self continuum, H2O foreign continuum, CO2, N2, and O2) (opacity_emission_level.py).</p> <p>All data are given in the spectral range from 10cm-1 to 3,250cm-1.</p> <p>This dataset is supplementary to the article "Effect of Uncertainty in Water Vapor Continuum Absorption on Radiative Forcing, Longwave Feedback and Climate Sensitivity" that has been submitted to Geophysical Research Letters (GRL).</p>This work was financially supported by the US National Science Foundation (award AGS-1916908) and by NOAA (award NA20OAR4310375)

Changes in the Tropical Lapse Rate due to Entrainment and Their Impact on Climate Sensitivity

The tropical temperature in the free troposphere deviates from a theoretical moist‐adiabat. The overall deviations are attributed to the entrainment of dry surrounding air. The deviations gradually approach zero in the upper troposphere, which we explain with a buoyancy‐sorting mechanism: the height to which individual convective parcels rise depends on parcel buoyancy, which is closely tied to the impact of entrainment during ascent. In higher altitudes, the temperature is increasingly controlled by the convective parcels that are warmer and more buoyant because of weaker entrainment effects. We represent such temperature deviations from moist‐adiabats in a clear‐sky one‐dimensional radiative‐convective equilibrium model. Compared with a moist‐adiabatic adjustment, having the entrainment‐induced temperature deviations lead to higher clear‐sky climate sensitivity. As the impact of entrainment depends on the saturation deficit, which increases with warming, our model predicts even more amplified surface warming from entrainment in a warmer climate.Plain Language Summary: The tropical temperature structure is determined by regions with deep convection, which is believed to be moist‐adiabatic. However, both models and observations show that the temperature deviates from moist‐adiabats. This is because convective parcels often mix with dry environmental air during ascent, pushing the temperature away from the moist‐adiabatic structure. More importantly, the tropical temperature is not dominated by one or a few strongest convective plumes, but rather controlled by the combined effect of many convective plumes of different strengths and depths. Therefore, the tropical temperature structure reflects the composition of convection happening at different values of boundary‐layer energy and mixing processes of variable efficiency with the environment. Using an idealized model, we find that representing such a deviation in the temperature structure increases the surface warming, because the resulting temperature lapse rate (LR) is more similar to a constant LR, showing less temperature increases higher than a moist‐adiabatic LR. This effect is likely amplified in a warmer climate due to this mixing process becoming more efficient in pushing the temperature further away from moist‐adiabats.Key Points: The tropical temperature profile in the free troposphere deviates from that following a moist‐adiabatic lapse rate (LR). The deviations from the moist‐adiabatic LR can be explained by entrainment with a buoyancy‐sorting mechanism. The temperature deviations from moist‐adiabats increase climate sensitivity.https://doi.org/10.5281/zenodo.1313687https://cds.climate.copernicus.eu/cdsapp#%21/dataset/reanalysis-era5-pressure-levels-monthly-means?tab=overviewhttps://esgf-data.dkrz.de/projects/cmip6-dkrz/http://hdl.handle.net/21.11116/0000-0008-FDA6-