Validation of a Large-Scale Simulated Brightness Temperature Dataset Using SEVIRI Satellite Observations

2009 ◽  
Vol 48 (8) ◽  
pp. 1613-1626 ◽  
Author(s):  
Jason A. Otkin ◽  
Thomas J. Greenwald ◽  
Justin Sieglaff ◽  
Hung-Lung Huang
Keyword(s):  
Brightness Temperature ◽  
Large Scale ◽  
Model Simulation ◽  
Probability Distributions ◽  
Relative Proportion ◽  
Tropical Convection ◽  
Radiative Properties ◽  
Model Errors ◽  
Ice Clouds ◽  
Brightness Temperatures

Abstract In this study, the accuracy of a simulated infrared brightness temperature dataset derived from a unique large-scale, high-resolution Weather Research and Forecasting (WRF) Model simulation is evaluated through a comparison with Spinning Enhanced Visible and Infrared Imager (SEVIRI) observations. Overall, the analysis revealed that the simulated brightness temperatures realistically depict many of the observed features, although several large discrepancies were also identified. The similar shapes of the simulated and observed probability distributions calculated for each infrared band indicate that the model simulation realistically depicted the cloud morphology and relative proportion of clear and cloudy pixels. A traditional error analysis showed that the largest model errors occurred over central Africa because of a general mismatch in the locations of deep tropical convection and intervening regions of clear skies and low-level cloud cover. A detailed inspection of instantaneous brightness temperature difference (BTD) imagery showed that the modeling system realistically depicted the radiative properties associated with various cloud types. For instance, thin cirrus clouds along the edges of deep tropical convection and within midlatitude cloud shields were characterized by much larger 10.8 − 12.0-μm BTD than optically thicker clouds. Simulated ice clouds were effectively discriminated from liquid clouds and clear pixels by the close relationship between positive 8.7 − 10.8-μm BTD and the coldest 10.8-μm brightness temperatures. Comparison of the simulated and observed BTD probability distributions revealed that the liquid and mixed-phase cloud-top properties were consistent with the observations, whereas the narrower BTD distributions for the colder 10.8-μm brightness temperatures indicated that the microphysics scheme was unable to simulate the full dynamic range of ice clouds.

scholarly journals Potential Impacts of Assimilating All-Sky Satellite Infrared Radiances on Convection-Permitting Analysis and Prediction of Tropical Convection

2020 ◽  
Vol 148 (8) ◽  
pp. 3203-3224
Author(s):  
Man-Yau Chan ◽  
Fuqing Zhang ◽  
Xingchao Chen ◽  
L. Ruby Leung
Keyword(s):  
Data Assimilation ◽  
Brightness Temperature ◽  
Large Scale ◽  
Spatial Scales ◽  
Tropical Convection ◽  
Tropical Oceans ◽  
Geostationary Meteorological Satellite ◽  
Infrared Radiances ◽  
Cloud Patterns ◽  
Dry Bias

Abstract Geostationary infrared satellite observations are spatially dense [>1/(20 km)2] and temporally frequent (>1 h−1). These suggest the possibility of using these observations to constrain subsynoptic features over data-sparse regions, such as tropical oceans. In this study, the potential impacts of assimilating water vapor channel brightness temperature (WV-BT) observations from the geostationary Meteorological Satellite 7 (Meteosat-7) on tropical convection analysis and prediction were systematically examined through a series of ensemble data assimilation experiments. WV-BT observations were assimilated hourly into convection-permitting ensembles using Penn State’s ensemble square root filter (EnSRF). Comparisons against the independently observed Meteosat-7 window channel brightness temperature (Window-BT) show that the assimilation of WV-BT generally improved the intensities and locations of large-scale cloud patterns at spatial scales larger than 100 km. However, comparisons against independent soundings indicate that the EnSRF analysis produced a much stronger dry bias than the no data assimilation experiment. This strong dry bias is associated with the use of the simulated WV-BT from the prior mean during the EnSRF analysis step. A stochastic variant of the ensemble Kalman filter (NoMeanSF) is proposed. The NoMeanSF algorithm was able to assimilate the WV-BT without causing such a strong dry bias and the quality of the analyses’ horizontal cloud pattern is similar to EnSRF’s analyses. Finally, deterministic forecasts initiated from the NoMeanSF analyses possess better horizontal cloud patterns above 500 km than those of the EnSRF. These results suggest that it might be better to assimilate all-sky WV-BT through the NoMeanSF algorithm than the EnSRF algorithm.

scholarly journals The Sun at millimeter wavelengths

2020 ◽  
Vol 635 ◽  
pp. A71 ◽  
Author(s):  
Sven Wedemeyer ◽  
Mikolaj Szydlarski ◽  
Shahin Jafarzadeh ◽  
Henrik Eklund ◽  
Juan Camilo Guevara Gomez ◽  
...  
Keyword(s):  
Brightness Temperature ◽  
Large Scale ◽  
Angular Resolution ◽  
Band 3 ◽  
Total Power ◽  
Small Scale ◽  
Solar Chromosphere ◽  
The Sun ◽  
Brightness Temperatures ◽  
Diagnostic Potential

Context. The Atacama Large Millimeter/submillimeter Array (ALMA) started regular observations of the Sun in 2016, first offering receiver Band 3 at wavelengths near 3 mm (100 GHz) and Band 6 at wavelengths around 1.25 mm (239 GHz). Aims. Here we present an initial study of one of the first ALMA Band 3 observations of the Sun. Our aim is to characterise the diagnostic potential of brightness temperatures measured with ALMA on the Sun. Methods. The observation covers a duration of 48 min at a cadence of 2 s targeting a quiet Sun region at disc-centre. Corresponding time series of brightness temperature maps are constructed with the first version of the Solar ALMA Pipeline and compared to simultaneous observations with the Solar Dynamics Observatory (SDO). Results. The angular resolution of the observations is set by the synthesised beam, an elliptical Gaussian that is approximately 1.4″ × 2.1″ in size. The ALMA maps exhibit network patches, internetwork regions, and elongated thin features that are connected to large-scale magnetic loops, as confirmed by a comparison with SDO maps. The ALMA Band 3 maps correlate best with the SDO/AIA 171 Å, 131 Å, and 304 Å channels in that they exhibit network features and, although very weak in the ALMA maps, imprints of large-scale loops. A group of compact magnetic loops is very clearly visible in ALMA Band 3. The brightness temperatures in the loop tops reach values of about 8000−9000 K and in extreme moments up to 10 000 K. Conclusions. ALMA Band 3 interferometric observations from early observing cycles already reveal temperature differences in the solar chromosphere. The weak imprint of magnetic loops and the correlation with the 171, 131, and 304 SDO channels suggests, however, that the radiation mapped in ALMA Band 3 might have contributions from a wider range of atmospheric heights than previously assumed, but the exact formation height of Band 3 needs to be investigated in more detail. The absolute brightness temperature scale as set by total power measurements remains less certain and must be improved in the future. Despite these complications and the limited angular resolution, ALMA Band 3 observations have a large potential for quantitative studies of the small-scale structure and dynamics of the solar chromosphere.

Evaluating the Accuracy of a High-Resolution Model Simulation through Comparison with MODIS Observations

2014 ◽  
Vol 53 (4) ◽  
pp. 1046-1058 ◽  
Author(s):  
Yong-Keun Lee ◽  
Jason A. Otkin ◽  
Thomas J. Greenwald
Keyword(s):  
High Resolution ◽  
Optical Thickness ◽  
Model Simulation ◽  
Probability Distributions ◽  
Wrf Model ◽  
Detailed Comparison ◽  
Cirrus Clouds ◽  
Radiative Properties ◽  
Radiative Transfer Model ◽  
Transfer Model

AbstractSynthetic infrared brightness temperatures (BTs) derived from a high-resolution Weather Research and Forecasting (WRF) model simulation over the contiguous United States are compared with Moderate Resolution Imaging Spectroradiometer (MODIS) observations to assess the accuracy of the model-simulated cloud field. A sophisticated forward radiative transfer model (RTM) is used to compute the synthetic MODIS observations. A detailed comparison of synthetic and real MODIS 11-μm BTs revealed that the model simulation realistically depicts the spatial characteristics of the observed cloud features. Brightness temperature differences (BTDs) computed for 8.5–11 and 11–12 μm indicate that the combined numerical model–RTM system realistically treats the radiative properties associated with optically thin cirrus clouds. For instance, much larger 11–12-μm BTDs occurred within thin clouds surrounding optically thicker, mesoscale cloud features. Although the simulated and observed BTD probability distributions for optically thin cirrus clouds had a similar range of positive values, the synthetic 11-μm BTs were much colder than observed. Previous studies have shown that MODIS cloud optical thickness values tend to be too large for thin cirrus clouds, which contributed to the apparent cold BT bias in the simulated thin cirrus clouds. Errors are substantially reduced after accounting for the observed optical thickness bias, which indicates that the thin cirrus clouds are realistically depicted during the model simulation.

scholarly journals Cloud Phase Characteristics Over Southeast Asia from A-Train Satellite Observations

2019 ◽  
Author(s):  
Yulan Hong ◽  
Larry Di Girolamo
Keyword(s):  
Southeast Asia ◽  
Brightness Temperature ◽  
Large Scale ◽  
Asian Monsoon ◽  
Large Population ◽  
Satellite Observations ◽  
The Other ◽  
Ice Clouds ◽  
Clear Sky ◽  
Climate Systems

Abstract. This study examines the climatological characteristics of cloud phase over Southeast Asia (SEA) based on A-Train satellite observations. Using the combined CloudSat-CALIPSO (CC) data, five main cloud groups are investigated: ice-only, ice-above-liquid, liquid-only, ice-above-mixed and mixed-only clouds that have annual mean frequencies of 27.8 %, 21.9 %, 16.9 %, 7.4 % and 6.2 %, respectively. Liquid-only clouds tend to occur in relatively cold, dry and stable environments. The other four cloud groups appear more frequently in relatively warm, humid and unstable conditions and their seasonal distributions move with large-scale climate systems: Asian monsoon and ITCZ. Liquid clouds are found to be highly inhomogeneous based on the heterogeneity index (Hσ) from Aqua MODIS, while ice-only and mixed-only clouds are often very smooth. Ice-above-liquid clouds are less inhomogeneous than liquid-only clouds due to the thin overlying ice clouds. Undetected subpixel liquid clouds enlarge clear sky Hσ, leading to some inhomogeneous clear sky pixels, which otherwise should be smooth. The reflectance at 0.645 (R0.645) and brightness temperature at 11 μm (BT11) of ice-only, liquid-only and ice-above-liquid clouds show peak frequencies near that of clear sky (R0.645 ~ 0.02, BT11 ~ 294 K), implying that a large population of thin or subpixel clouds over SEA are difficult to see by MODIS. The CC data also show abundant thin clouds over SEA, which indicates 78.3 % ice-only and 89.6 % ice-above-liquid clouds with ice τ 

INFLUENCE OF REGULARITY OF SATELLITE MICROWAVE RADIOMETER MEASUREMENTS ON THE ACCURACY OF BRIGHTNESS TEMPERATURE REPRODUCTION IN AREAS OF THE TROPICAL CYCLONES

2021 ◽  
pp. 78-85
Author(s):  
А. G. Grankov ◽  
◽  
А. А. Milshin ◽  
Keyword(s):  
Brightness Temperature ◽  
Tropical Cyclones ◽  
Microwave Radiometer ◽  
Measurement Data ◽  
Hurricane Wilma ◽  
Brightness Temperatures ◽  
Atmosphere System ◽  
Ocean Atmosphere ◽  
The Caribbean ◽  
Satellite Microwave

An accuracy of reproduction of daily variations in the ocean–atmosphere system brightness temperature in the areas of development and movement of tropical hurricanes in the Caribbean Sea and Gulf of Mexico is analyzed. The analysis is based on the data of single and group satellite microwave radiometer measurements. The results are obtained using archival measurement data of SSM/I radiometers from the F11, F13, F14, and F15 DMSP satellites during the period of existence of tropical hurricanes Bret and Wilma. An example is given to demonstrate the use of daily brightness temperatures obtained from DMSP satellites for monitoring the development and propagation of hurricane Wilma.

LESbrary: A library of large eddy simulation data for the calibration and uncertainty quantification of ocean surface boundary layer turbulence parameterizations

2021 ◽  
Author(s):  
Gregory Wagner ◽  
Andre Souza ◽  
Adeline Hillier ◽  
Ali Ramadhan ◽  
Raffaele Ferrari
Keyword(s):  
Boundary Layer ◽  
Turbulent Mixing ◽  
Large Scale ◽  
Ocean Surface ◽  
Limited Area ◽  
Surface Boundary ◽  
Model Errors ◽  
Surface Boundary Layer ◽  
Large Eddy ◽  
Free Parameters

<p>Parameterizations of turbulent mixing in the ocean surface boundary layer (OSBL) are key Earth System Model (ESM) components that modulate the communication of heat and carbon between the atmosphere and ocean interior. OSBL turbulence parameterizations are formulated in terms of unknown free parameters estimated from observational or synthetic data. In this work we describe the development and use of a synthetic dataset called the “LESbrary” generated by a large number of idealized, high-fidelity, limited-area large eddy simulations (LES) of OSBL turbulent mixing. We describe how the LESbrary design leverages a detailed understanding of OSBL conditions derived from observations and large scale models to span the range of realistically diverse physical scenarios. The result is a diverse library of well-characterized “synthetic observations” that can be readily assimilated for the calibration of realistic OSBL parameterizations in isolation from other ESM model components. We apply LESbrary data to calibrate free parameters, develop prior estimates of parameter uncertainty, and evaluate model errors in two OSBL parameterizations for use in predictive ESMs.</p>

scholarly journals Assimilation of SMOS brightness temperatures or soil moisture retrievals into a land surface model

2016 ◽  
Vol 20 (12) ◽  
pp. 4895-4911 ◽  
Author(s):  
Gabriëlle J. M. De Lannoy ◽  
Rolf H. Reichle
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Surface Soil ◽  
Root Zone ◽  
Incidence Angle ◽  
Land Surface Model ◽  
Surface Model ◽  
Model Errors ◽  
Surface Soil Moisture ◽  
Brightness Temperatures

Abstract. Three different data products from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated separately into the Goddard Earth Observing System Model, version 5 (GEOS-5) to improve estimates of surface and root-zone soil moisture. The first product consists of multi-angle, dual-polarization brightness temperature (Tb) observations at the bottom of the atmosphere extracted from Level 1 data. The second product is a derived SMOS Tb product that mimics the data at a 40° incidence angle from the Soil Moisture Active Passive (SMAP) mission. The third product is the operational SMOS Level 2 surface soil moisture (SM) retrieval product. The assimilation system uses a spatially distributed ensemble Kalman filter (EnKF) with seasonally varying climatological bias mitigation for Tb assimilation, whereas a time-invariant cumulative density function matching is used for SM retrieval assimilation. All assimilation experiments improve the soil moisture estimates compared to model-only simulations in terms of unbiased root-mean-square differences and anomaly correlations during the period from 1 July 2010 to 1 May 2015 and for 187 sites across the US. Especially in areas where the satellite data are most sensitive to surface soil moisture, large skill improvements (e.g., an increase in the anomaly correlation by 0.1) are found in the surface soil moisture. The domain-average surface and root-zone skill metrics are similar among the various assimilation experiments, but large differences in skill are found locally. The observation-minus-forecast residuals and analysis increments reveal large differences in how the observations add value in the Tb and SM retrieval assimilation systems. The distinct patterns of these diagnostics in the two systems reflect observation and model errors patterns that are not well captured in the assigned EnKF error parameters. Consequently, a localized optimization of the EnKF error parameters is needed to further improve Tb or SM retrieval assimilation.

scholarly journals Wind speed response of marine non-precipitating stratocumulus clouds over a diurnal cycle in cloud-system resolving simulations

2016 ◽  
Vol 16 (9) ◽  
pp. 5811-5839 ◽  
Author(s):  
Jan Kazil ◽  
Graham Feingold ◽  
Takanobu Yamaguchi
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Large Scale ◽  
Layer Growth ◽  
Radiative Properties ◽  
Cloud Base ◽  
Latent Heat Release ◽  
Marine Stratocumulus ◽  
Stratocumulus Clouds ◽  
Boundary Layer Growth

Abstract. Observed and projected trends in large-scale wind speed over the oceans prompt the question: how do marine stratocumulus clouds and their radiative properties respond to changes in large-scale wind speed? Wind speed drives the surface fluxes of sensible heat, moisture, and momentum and thereby acts on cloud liquid water path (LWP) and cloud radiative properties. We present an investigation of the dynamical response of non-precipitating, overcast marine stratocumulus clouds to different wind speeds over the course of a diurnal cycle, all else equal. In cloud-system resolving simulations, we find that higher wind speed leads to faster boundary layer growth and stronger entrainment. The dynamical driver is enhanced buoyant production of turbulence kinetic energy (TKE) from latent heat release in cloud updrafts. LWP is enhanced during the night and in the morning at higher wind speed, and more strongly suppressed later in the day. Wind speed hence accentuates the diurnal LWP cycle by expanding the morning–afternoon contrast. The higher LWP at higher wind speed does not, however, enhance cloud top cooling because in clouds with LWP ⪆ 50 g m−2, longwave emissions are insensitive to LWP. This leads to the general conclusion that in sufficiently thick stratocumulus clouds, additional boundary layer growth and entrainment due to a boundary layer moistening arises by stronger production of TKE from latent heat release in cloud updrafts, rather than from enhanced longwave cooling. We find that large-scale wind modulates boundary layer decoupling. At nighttime and at low wind speed during daytime, it enhances decoupling in part by faster boundary layer growth and stronger entrainment and in part because shear from large-scale wind in the sub-cloud layer hinders vertical moisture transport between the surface and cloud base. With increasing wind speed, however, in decoupled daytime conditions, shear-driven circulation due to large-scale wind takes over from buoyancy-driven circulation in transporting moisture from the surface to cloud base and thereby reduces decoupling and helps maintain LWP. The total (shortwave + longwave) cloud radiative effect (CRE) responds to changes in LWP and cloud fraction, and higher wind speed translates to a stronger diurnally averaged total CRE. However, the sensitivity of the diurnally averaged total CRE to wind speed decreases with increasing wind speed.

scholarly journals Cluster analysis of midlatitude oceanic cloud regimes: mean properties and temperature sensitivity

2010 ◽  
Vol 10 (13) ◽  
pp. 6435-6459 ◽  
Author(s):  
N. D. Gordon ◽  
J. R. Norris
Keyword(s):  
Large Scale ◽  
Longwave Radiation ◽  
Cloud Fraction ◽  
Climate System ◽  
Radiative Properties ◽  
Upper Troposphere ◽  
Low Level ◽  
Increasing Temperature ◽  
Cloud Regimes ◽  
Cloud Response

Abstract. Clouds play an important role in the climate system by reducing the amount of shortwave radiation reaching the surface and the amount of longwave radiation escaping to space. Accurate simulation of clouds in computer models remains elusive, however, pointing to a lack of understanding of the connection between large-scale dynamics and cloud properties. This study uses a k-means clustering algorithm to group 21 years of satellite cloud data over midlatitude oceans into seven clusters, and demonstrates that the cloud clusters are associated with distinct large-scale dynamical conditions. Three clusters correspond to low-level cloud regimes with different cloud fraction and cumuliform or stratiform characteristics, but all occur under large-scale descent and a relatively dry free troposphere. Three clusters correspond to vertically extensive cloud regimes with tops in the middle or upper troposphere, and they differ according to the strength of large-scale ascent and enhancement of tropospheric temperature and humidity. The final cluster is associated with a lower troposphere that is dry and an upper troposphere that is moist and experiencing weak ascent and horizontal moist advection. Since the present balance of reflection of shortwave and absorption of longwave radiation by clouds could change as the atmosphere warms from increasing anthropogenic greenhouse gases, we must also better understand how increasing temperature modifies cloud and radiative properties. We therefore undertake an observational analysis of how midlatitude oceanic clouds change with temperature when dynamical processes are held constant (i.e., partial derivative with respect to temperature). For each of the seven cloud regimes, we examine the difference in cloud and radiative properties between warm and cold subsets. To avoid misinterpreting a cloud response to large-scale dynamical forcing as a cloud response to temperature, we require horizontal and vertical temperature advection in the warm and cold subsets to have near-median values in three layers of the troposphere. Across all of the seven clusters, we find that cloud fraction is smaller and cloud optical thickness is mostly larger for the warm subset. Cloud-top pressure is higher for the three low-level cloud regimes and lower for the cirrus regime. The net upwelling radiation flux at the top of the atmosphere is larger for the warm subset in every cluster except cirrus, and larger when averaged over all clusters. This implies that the direct response of midlatitude oceanic clouds to increasing temperature acts as a negative feedback on the climate system. Note that the cloud response to atmospheric dynamical changes produced by global warming, which we do not consider in this study, may differ, and the total cloud feedback may be positive.

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