Actual Satellite Observations Research Articles

Radiative effects of observationally constrained tropical upper-level clouds in a radiative-convective equilibrium model

Tropical upper-level clouds (TUCs) control the radiation budget in a climate system and strongly influence surface temperatures. This study examines global mean surface temperature changes due to the percent change in TUC cover, which is referred to as the tropical upper-level cloud radiative effect (TUCRE, in units of Kelvin per %). We use a radiative-convective equilibrium model that can control both upper- and lower-level cloud layers separately in three idealized regions (extratropics, tropical moist, and tropical dry regions) and two sub-regions (clear-moist and cloudy-moist regions) within the tropical moist regions. In the simulation, tropical reflectivity based on the TUC fraction assumes a primary role in determining the TUCRE. Accurate estimate of the TUCRE requires careful prescriptions according to actual satellite observations. We use the extent of TUC fraction and reflectivity obtained from 18 years (2003–2020) of satellite data on daily MODIS cloud properties. Our results show that the estimated net TUCRE ranges from 0.19 to 0.33 K/%, with a higher TUC fraction leading to higher temperatures (a warming effect) in the climate system. This means that a longwave TUCRE dominates over a shortwave TUCRE. When upper- and lower-level clouds interplay in the model, the range of the TUCRE was greater with a combination of two cloud layers, although all values were positive. The TUCRE is greater by 0.22 to 0.40 K/% when upper- and lower-level clouds are negatively coupled, because the Earth warms due to a decline in the reflectance of solar radiation. When upper- and lower-level clouds are positively coupled, the TUCRE is lower by 0.14 to 0.30 K/%, as less radiation reaches the Earth through combined cloud layers. Finally, we test the sensitivity of the TUCRE with five TUC fractions and 15 combinations of tropical reflectivity. Comparing our results with the TUCREs estimated from climate models will help us understand how TUC cover affects climate, and should greatly reduce uncertainty associated with cloud feedback.

Impact of all‐sky water vapour channel radiance from INSAT‐3D/3DR satellite over South Asia region using WRF model

AbstractThe objective of this study is to explore and present a methodology to assimilate all‐sky water vapour (WV) radiance from Indian geostationary satellites (INSAT‐3D and INSAT‐3DR) in the Weather Research and Forecasting (WRF) model. For all‐sky assimilation, hydrometeors are considered as control variables by adding in background error covariance. Additionally, this study uses the application of Global Satellite based Inter‐Calibration System (GSICS) based bias correction mechanism on WV radiances before their assimilation. To fulfil these objectives, three sets of experiments have been performed with and without WV radiance assimilation for the month of July 2018 over the South Asia region. The impact assessment of assimilation has been performed by comparing radiative transfer (RT) model‐simulated analysed and predicted brightness temperature against independent satellite observations from SAPHIR (Sondeur Atmosphérique du Profil d'Humidité Intertropicale par Radiométrie) and MHS (Microwave Humidity Sounder) sensors. Results not only show the number of assimilated observations increased significantly (∼250%) in all‐sky assimilation compared to clear‐sky assimilation but also present that the all‐sky analyses are closer to actual satellite observations. Due to the multivariate nature of variational data assimilation, noteworthy changes are also noticed in hydrometeors analyses in all‐sky assimilation. The short‐range forecasts confirm the positive impact of all‐sky assimilation as compared to clear‐sky assimilation when verified against SAPHIR and MHS measurements.

Impact of Microphysical Parameterizations on Simulated Hurricanes—Using Multi-Parameter Satellite Data to Determine the Particle Size Distributions that Produce Most Realistic Storms

Understanding and forecasting hurricanes remains a challenge for the operational and research communities. To accurately predict the Tropical Cyclone (TC) evolution requires properly reflecting the storm’s inner core dynamics by using: (i) high-resolution models; (ii) realistic physical parameterizations. The microphysical processes and their representation in cloud-permitting models are of crucial importance. In particular, the assumed Particle Size Distribution (PSD) functions affect nearly all formulated microphysical processes and are among the most fundamental assumptions in the bulk microphysics schemes. This paper analyzes the impact of the PSD assumptions on simulated hurricanes and their synthetic radiometric signatures. It determines the most realistic, among the available set of assumptions, based on comparison to multi-parameter satellite observations. Here we simulated 2005′s category-5 Hurricane Rita using the cloud-permitting community Weather Research and Forecasting model (WRF) with two different microphysical schemes and with seven different modifications of the parametrized hydrometeor properties within one of the two schemes. We then used instrument simulators to produce satellite-like observations. The study consisted in evaluating the structure of the different simulated storms by comparing, for each storm, the calculated microwave signatures with actual satellite observations made by (a) the passive microwave radiometer that was carried by the Tropical Rainfall Measuring Mission (TRMM) satellite—the TRMM microwave imager TMI, (b) TRMM’s precipitation radar (PR) and (c) the ocean-wind-vector scatterometer carried by the QuikSCAT satellite. The analysis reveals that the different choices of microphysical parameters do produce significantly different microwave signatures, allowing an objective determination of a “best” parameter combination whose resulting signatures are collectively most consistent with the wind and precipitation observations obtained from the satellites. In particular, we find that assuming PSDs with larger number of smaller hydrometeors produces storms that compare best to observations.

Local Impact of Stochastic Shallow Convection on Clouds and Precipitation in the Tropical Atlantic

AbstractThe local impact of stochastic shallow convection on clouds and precipitation is tested in a case study over the tropical Atlantic on 20 December 2013 using the Icosahedral Nonhydrostatic Model (ICON). ICON is used at a grid resolution of 2.5 km and is tested in several configurations that differ in their treatment of shallow convection. A stochastic shallow convection scheme is compared to the operational deterministic scheme and a case with no representation of shallow convection. The model is evaluated by comparing synthetically generated irradiance data for both visible and infrared wavelengths against actual satellite observations. The experimental approach is designed to distinguish the local effects of parameterized shallow convection (or lack thereof) within the trades versus the ITCZ. The stochastic cases prove to be superior in reproducing low-level cloud cover, deep convection, and its organization, as well as the distribution of precipitation in the tropical Atlantic ITCZ. In these cases, convective heating in the subcloud layer is substantial, and boundary layer depth is increased as a result of the heating, while evaporation is enhanced at the expense of sensible heat flux at the ocean’s surface. The stochastic case where subgrid shallow convection is deactivated below the resolved deep updrafts indicates that local boundary layer convection is crucial for a better representation of deep convection. Based on these results, our study points to a necessity to further develop parameterizations of shallow convection for use at the convection-permitting resolutions and to assuredly include them in weather and climate models even as their imperfect versions.

Cirrus clouds that adversely affect Landsat 8 images: What are they and how to detect them?

We developed an algorithm called Cmask (Cirrus cloud mask) for cirrus cloud detection in Landsat 8 imagery using time series of Cirrus Band (1.36–1.39 μm) observations. For each pixel, a harmonic model, which includes a water vapor regressor, based on all available Cirrus Band observations is estimated using the Robust Iteratively Reweighted Least Squares (RIRLS) regression approach, and pixels affected by cirrus cloud are identified by comparing model predictions and actual satellite observations of the Cirrus Band Top-Of-Atmosphere (TOA) reflectance. Furthermore, we analyzed the effect of increasing Cirrus Band TOA reflectance on the surface reflectance of the Blue, Green, Red, Near Infrared (NIR), and two Shortwave Infrared (SWIR) (SWIR 1 and SWIR 2) Bands based on a set of globally distributed random samples. The goal of this study is to answer the question of what are cirrus clouds in the context of a Landsat observation, or more specifically, when should we identify a pixel as cirrus cloud such that we know the reflectance in the other spectral bands has been seriously affected by cirrus clouds. The challenge is to then develop a simple and operational algorithm for accurate detection of cirrus clouds in Landsat 8 images. The Cmask algorithm reduced almost by half the errors found in the U.S. Geological Survey (USGS) Quality Assessment (QA) Band for distinguishing cirrus cloud and clear observations (8% versus 15% error).

Application of machine learning to hyperspectral radiative transfer simulations

Hyperspectral observations have become one of the most popular and powerful methods for atmospheric remote sensing, and are widely used for temperature, gas, aerosol, and cloud retrievals. However, accurate forward radiative transfer simulations are computationally expensive since typical line-by-line approaches involve a large number of monochromatic radiative transfer calculations. This study explores the feasibility of machine learning techniques (using neural network (NN) as an example) for fast hyperspectral radiative transfer simulations, by performing calculations at a small fraction of hyperspectral wavelengths and extending them across the entire spectral range. Results from the NN model are compared with those from a principal component analysis (PCA) model, which uses a similar principle of dimensionality reduction. We consider hyperspectral radiances from both actual satellite observations and accurate line-by-line simulations. The NN model can alleviate the computational burden by two to three orders of magnitude, and generate radiances with small relative errors (generally less than 0.5% compared to exact calculations); the performance of the NN model is better than that of the PCA model. The model can be further improved by optimizing the training procedure and parameters, the representative wavelengths, and the machine learning technique itself.

SUPPORTING MANAGEMENT OF EUROPEAN REFUGEE STREAMS BY EARTH OBSERVATION AND GEOINFORMATION

Abstract. The sharp increase in refugee numbers arriving in the European Union has recently caused major and manifold challenges for the member states and their administrative services. Location based situation reports and maps may support the refugee management from local to European level. The first support is mapping of the geographical distribution of migrating people which needs more or less real time data. The actual data sources are location related observations along the routes of refugees, actual satellite observations and data mining results. These tools and data are used to monitor spatial distributions as well as extrapolate the arrival of refugees for the subsequent weeks. The second support is the short term update of the location of initial registration facilities and first reception facilities, their capacities, and their occupancy. The third management level is the systematic inquiry for unoccupied housing facilities and for empty places within build-up areas. Geo-coded data sets of house numbers have to be cross-referenced with city maps and communal inhabitants address data. The legal aspects of data mining and secured access to personal data are strictly controlled by the administration allowing only limited access and distribution of data and results. However, the paper will not disclose scientific progress in Earth Observation and GIS, but will actually demonstrate an urgently needed new combination of existing methods to support actual needs. The societal benefits of EO/GIS are no longer just potential possibilities, but actual results in real political, administrative and humanitarian day to day reality.

SUPPORTING MANAGEMENT OF EUROPEAN REFUGEE STREAMS BY EARTH OBSERVATION AND GEOINFORMATION

The sharp increase in refugee numbers arriving in the European Union has recently caused major and manifold challenges for the member states and their administrative services. Location based situation reports and maps may support the refugee management from local to European level. The first support is mapping of the geographical distribution of migrating people which needs more or less real time data. The actual data sources are location related observations along the routes of refugees, actual satellite observations and data mining results. These tools and data are used to monitor spatial distributions as well as extrapolate the arrival of refugees for the subsequent weeks. The second support is the short term update of the location of initial registration facilities and first reception facilities, their capacities, and their occupancy. The third management level is the systematic inquiry for unoccupied housing facilities and for empty places within build-up areas. Geo-coded data sets of house numbers have to be cross-referenced with city maps and communal inhabitants address data. The legal aspects of data mining and secured access to personal data are strictly controlled by the administration allowing only limited access and distribution of data and results. However, the paper will not disclose scientific progress in Earth Observation and GIS, but will actually demonstrate an urgently needed new combination of existing methods to support actual needs. The societal benefits of EO/GIS are no longer just potential possibilities, but actual results in real political, administrative and humanitarian day to day reality.

Short-Term and Long-Term Variability of Antenna Position Due to Thermal Bending of Pillar Monument at Permanent GNSS Station

Abstract The variability of daily site coordinates at permanent GNSS station is a sum of many disturbing factors influencing the actual satellite observations, data processing, and bias modelling. In the paper are analysed possibilities of monitoring the instability of GNSS antenna pillar monument by the independent observations using the precise inclination sensor. Long-term series from three different types of pillars show specific features in amplitude and temporal evolution of monument bending. Correlations with daily temperature and/or solar radiation changes were proved.

Propagation of plasmoids generated by fast reconnection in the geomagnetic tail

So-called plasmoids are most fundamental signatures of geomagnetic substorms, and precise measurements of magnetic fields have been obtained by in situ satellite observations. Hence, in understanding substorm phenomena, it is essential to clarify the physical mechanism of plasmoid dynamics. The present paper studies on the basis of the spontaneous fast reconnection model how a large-scale plasmoid is generated and propagates in weakly sheared current sheets. It is demonstrated that the basic structure and dynamics of the plasmoid, generated by the fast reconnection, are both qualitatively and quantitatively in good agreement with actual satellite observations. In particular, magnetic field lines inside the generated plasmoid deviate from a helical geometry.

Virtual satellite observations of plasmoids generated by fast reconnection in the geomagnetic tail

Abstract. The present paper studies fundamental features of plasmoid propagation by virtual satellite observations in the simulation box. The plasmoid domain is divided into the plasmoid reconnection region P, where magnetized plasmas with reconnected field lines, heated by dissipation mechanisms of fast reconnection, are accumulated, and the plasmoid core region C, where magnetized plasmas with sheared field lines, initially embedded in the current sheet, is adiabatically compressed. When the virtual satellite is located in a position through which the plasmoid core region passes, it detects distinct changes in quantities at the interface between the regions P and C, where the north-south field component Bz has the bipolar profile and the sheared field component By has the peak value. The observed magnetic field profile is, both quantitatively and qualitatively, in good agreement with the standard one detected by actual satellite observations, although when the satellite location is very close to the X neutral line, where reconnection occurs, the Bz field profile becomes dipolarization-like rather than bipolar. If the satellite detects only the plasmoid region P outside region C, the standard magnetic field profile becomes obscure even if notable plasmoid signatures, such as enhanced plasma temperature and plasma flow, are observed. Unlike the traditional flux rope model based on multiple reconnections, it is demonstrated that the standard magnetic field profile, observed for plasmoids propagating in the geomagnetic tail, is the direct outcome of the single fast reconnection evolution.

Numerical studies on three‐dimensional earthward fast plasma flows in the near‐Earth plasma sheet by the spontaneous fast reconnection model

The spontaneous fast reconnection model is applied to the earthward fast flow events observed in the near‐Earth plasma sheet. Here, the earthward fast flow events include both of bursty bulk flow events and flow burst events. In order to apply it directly to actual observations, virtual probes are located in the plasma sheet region in the three‐dimensional simulation domain so that we can directly observe the temporal variations of plasma quantities in accordance with the growth and proceeding of the fast reconnection. In this model, magnetic reconnection drastically evolves and Alfvénic fast plasma jet flows in the very restricted narrow channel, and a large‐scale plasmoid is formed ahead of the fast plasma jet. The results of virtual observation of these evolutions are found to be in good agreement with actual satellite observations. At the same time, in the lobe region, travelling compression regions (TCRs) are observed in connection with the fast flow events. The temporal profiles of magnetic fields detected by the virtual probes are also in good agreement with actual satellite observations. It is concluded that the earthward fast flow events and earthward TCR events result from the fast reconnection mechanism.

Technical note: A new day- and night-time Meteosat Second Generation Cirrus Detection Algorithm MeCiDA

Abstract. A new cirrus detection algorithm for the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) aboard the geostationary Meteosat Second Generation (MSG), MeCiDA, is presented. The algorithm uses the seven infrared channels of SEVIRI and thus provides a consistent scheme for cirrus detection at day and night. MeCiDA combines morphological and multi-spectral threshold tests and detects optically thick and thin ice clouds. The thresholds were determined by a comprehensive theoretical study using radiative transfer simulations for various atmospheric situations as well as by manually evaluating actual satellite observations. The cirrus detection has been optimized for mid- and high latitudes but it could be adapted to other regions as well. The retrieved cirrus masks have been validated by comparison with the Moderate Resolution Imaging Spectroradiometer (MODIS) Cirrus Reflection Flag. To study possible seasonal variations in the performance of the algorithm, one scene per month of the year 2004 was randomly selected and compared with the MODIS flag. 81% of the pixels were classified identically by both algorithms. In a comparison of monthly mean values for Europe and the North-Atlantic MeCiDA detected 29.3% cirrus coverage, while the MODIS SWIR cirrus coverage was 38.1%. A lower detection efficiency is to be expected for MeCiDA, as the spatial resolution of MODIS is considerably better and as we used only the thermal infrared channels in contrast to the MODIS algorithm which uses infrared and visible radiances. The advantage of MeCiDA compared to retrievals for polar orbiting instruments or previous geostationary satellites is that it permits the derivation of quantitative data every 15 min, 24 h a day. This high temporal resolution allows the study of diurnal variations and life cycle aspects. MeCiDA is fast enough for near real-time applications.

A Fast Cloud Overlap Parameterization for Microwave Radiance Assimilation

Abstract The assimilation of cloud- and rain-affected radiances in numerical weather prediction systems requires fast and accurate radiative transfer models. One of the largest sources of modeling errors originates from the assumptions regarding the vertical and horizontal subgrid-scale variability of model clouds and precipitation. In this work, cloud overlap assumptions are examined in the context of microwave radiative transfer and used to develop an accurate reference model. A fast cloud overlap algorithm is presented that allows for the accurate simulation of microwave radiances with a small number of radiative transfer calculations. In particular, the errors for a typical two-column approach currently used operationally are found to be relatively large for many cases of cloudy fields containing precipitation, even those with an overall cloud fraction of unity; these errors are largely eliminated by using the new approach presented here, at the cost of a slight increase in computation time. Radiative transfer cloud overlap errors are also evident in simulations when compared to actual satellite observations, in that the biases are somewhat reduced when applying a more accurate treatment of cloud overlap.

Parametric studies on traveling compression regions observed in the Earth’s magnetotail

On the basis of the spontaneous fast reconnection model, the traveling compression region (TCR) is studied by magnetohydrodynamic simulations for various plasma parameters. Once the fast reconnection mechanism involving slow shocks builds up, the general features of TCR, observed by virtual satellites located in the simulation box, are in good agreement with actual satellite observations. Quantitatively, the TCR signature is not significantly influenced by plasma β, whereas its duration time is proportional to VAe−1, where VAe is the Alfvén velocity in the magnetic field region; also, the compression ratio of TCR is larger for the smaller plasma density ρe in the magnetic field region because of larger compressibility. In the diffusion region, resistive tearing is likely to occur, giving rise to multiple small-scale TCRs following the major TCR. For the uniform resistivity model, where the fast reconnection mechanism is not realized, any TCR signature cannot be observed. Hence, the TCR signature, observed in association with substorms, provides a definite evidence such that the fast reconnection mechanism is realized in the Earth’s magnetotail.

Modeling of traveling compression regions in the Earth’s magnetotail by the spontaneous fast reconnection model

The spontaneous fast reconnection model is applied to the traveling compression regions (TCRs) observed in the Earth’s magnetotail lobe region in association with substorms. For this purpose, virtual satellites are located at spatial points in the (low-β) magnetic field region in the three-dimenisonal simulation domain, so that each satellite directly observes the temporal variations of magnetic fields, obtained from simulations, in accordance with the growth and proceeding of the fast reconnection mechanism. If the virtual satellite is located ahead of the initial plasmoid formation, it observes a pulse-like field compression with the compression rate of more than 10% as well as the bipolar structure of the magnetic field component from northward to southward tilting, when the plasmoid center passes through the satellite location. On the other hand, if it is located behind the plasmoid formation, it observes the unipolar structure of the southward field component. The simulation results are shown to be, both quantitatively and qualitatively, in good agreement with the actual satellite observations. It is demonstrated that the TCR event is the fast reconnection mechanism itself that is seen in the ambient (low-β) magnetic field (magnetotail lobe) region.

Determination of cloud and precipitation characteristics in the monsoon region using satellite microwave and infrared observations

We have studied the cloud and precipitation features in the Indian summer monsoon region based on satellite microwave and infrared observations. Emphases are particularly given to the differences between stratiform and convective rains and between rains over land and over ocean. In the studied region, average rainfall rate of convective clouds is about 6 times higher than for stratiform clouds while the latter covers 4 to 5 times more area than the former. As a result, convective rains produce higher rain total than stratiform rains with a ratio of about 3 : 2. The difference between convective and stratiform rains is evident virtually by any satellite signatures – cloud top temperature, and microwave emission, scattering and combined signatures. Cloud top temperature appears no skill to reflect surface rainfall rates for stratiform rains while colder cloud top temperatures correspond to higher rainfall rates for convective clouds. As rainfall rate increases, microwave emission signature reaches saturation much quicker for stratiform rains than for convective rains. For convective rains, the rainfall rate – scattering signature relation shows a distinct difference between rains over land and over ocean. Corresponding to the same rainfall rate, the scattering signature over land is about twice as high as that over ocean. The mean vertical precipitation profiles showed that stratiform rains have a constant rainfall rate below freezing level and a sharp drop-off above, regardless over land or ocean. Convective rain profiles, on the other hand, often have the maximum rainfall rate below the freezing level, implying a significant growth of raindrops by warm microphysical processes, such as coalescence. It is also found that given the same surface rainfall rate, the amount of ice particles above freezing level is substantially greater for convective rains over land than over ocean, which explains the difference of scattering signatures between rains over the two different surface types. It is also demonstrated that the sub-pixel variability of rains is largely responsible for the mismatch between plane-parallel model simulations and actual satellite observations.

Diurnal Radiance Patterns of Finite and Semi-Infinite Clouds in Observations of Cloud Fields

One of the important radiative effects of cloud Shape is to modify diurnal radiance patterns observed from satellites. Theory predicts a diurnal radiance pattern nearly symmetric about local noon for both semi-infinite and finite clouds situated on the equator at the equinox with a satellite directly overhead. For a geostationary satellite (SMS-1) located to the west of the cloud, the semi-infinite cloud still products a pattern nearly symmetric about local noon while finite cubic clouds produce a distinctly different pattern which peaks during the afternoon. Simulated diurnal satellite observations of a finite cubic and semi-infinite cloud were compared with actual diurnal satellite observations of cloud fields with cloud cover varying from less than 30% to greater than 90%. The results for 4 n mi resolution data from the two observed cloud fields demonstrate that the diurnal radiance patterns of both semi-infinite and finite clouds exist in satellite observations. Degrading the resolution to 16 n mi did not significantly alter the semi-infinite or finite diurnal radiance pattern of either observed cloud field. The effects of cloud shape on satellite observations have potential application to problems in data interpretation, cloud cover determination, albedo calculations and identification of cloud fields.

IMF sector behavior deduced from geomagnetic data

Interplanetary magnetic field (IMF) sector structures, such as ‘toward’ the sun and ‘away’ from the sun on each day, have been objectively estimated from daily and monthly mean values of the horizontal component of the geomagnetic variation field at Godhavn during the period 1926–1970. The agreement between this estimation and actual satellite observations of the sector structures of the interval 1964‐1970 is 88, 79, and 58% in summer, equinox, and winter, respectively. A remarkable agreement (more than 95%) is obtained for the summers of 1964, 1969, and 1970. Various types of IMF sector behavior are examined by taking this seasonal factor into consideration. Approximately 27‐day recurrences of the same structure are often found, and 5‐ to 14‐day consecutive occurrences of the same sector are frequently noted. Furthermore, the total number of occurrences for each estimated sector in each year shows an apparently good correlation with smoothed sunspot numbers and geomagnetic aa index. After a brief introduction of the production mechanism of sector effects on polar geomagnetic fields the limitations and merits of IMF sector inference from geomagnetic data are emphasized.