A Physically Based Algorithm for Non-Blackbody Correction of Cloud-Top Temperature and Application to Convection Study

2014 ◽  
Vol 53 (7) ◽  
pp. 1844-1857 ◽  
Author(s):  
Chunpeng Wang ◽  
Zhengzhao Johnny Luo ◽  
Xiuhong Chen ◽  
Xiping Zeng ◽  
Wei-Kuo Tao ◽  
...  
Keyword(s):  
Brightness Temperature ◽  
Weighting Function ◽  
Convective Cloud ◽  
Transfer Model ◽  
Height Range ◽  
Convective Clouds ◽  
Physically Based ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference ◽  
Cloud Top Temperature

AbstractCloud-top temperature (CTT) is an important parameter for convective clouds and is usually different from the 11-μm brightness temperature due to non-blackbody effects. This paper presents an algorithm for estimating convective CTT by using simultaneous passive [Moderate Resolution Imaging Spectroradiometer (MODIS)] and active [CloudSat + Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)] measurements of clouds to correct for the non-blackbody effect. To do this, a weighting function of the MODIS 11-μm band is explicitly calculated by feeding cloud hydrometer profiles from CloudSat and CALIPSO retrievals and temperature and humidity profiles based on ECMWF analyses into a radiation transfer model. Among 16 837 tropical deep convective clouds observed by CloudSat in 2008, the averaged effective emission level (EEL) of the 11-μm channel is located at optical depth ~0.72, with a standard deviation of 0.3. The distance between the EEL and cloud-top height determined by CloudSat is shown to be related to a parameter called cloud-top fuzziness (CTF), defined as the vertical separation between −30 and 10 dBZ of CloudSat radar reflectivity. On the basis of these findings a relationship is then developed between the CTF and the difference between MODIS 11-μm brightness temperature and physical CTT, the latter being the non-blackbody correction of CTT. Correction of the non-blackbody effect of CTT is applied to analyze convective cloud-top buoyancy. With this correction, about 70% of the convective cores observed by CloudSat in the height range of 6–10 km have positive buoyancy near cloud top, meaning clouds are still growing vertically, although their final fate cannot be determined by snapshot observations.

scholarly journals Frequency of deep convective clouds in the tropical zone from 10 years of AIRS data

2013 ◽  
Vol 13 (21) ◽  
pp. 10795-10806 ◽  
Author(s):  
H. H. Aumann ◽  
A. Ruzmaikin
Keyword(s):  
Brightness Temperature ◽  
Frequency Of Occurrence ◽  
Tropical Zone ◽  
Convective Clouds ◽  
The Past ◽  
Atmospheric Window ◽  
Deep Convective Clouds ◽  
Sst Anomaly ◽  
The Difference ◽  
Global Precipitation

Abstract. Deep convective clouds (DCCs) have been widely studied because of their association with heavy precipitation and severe weather events. Changes in the properties of DCCs are likely in a changing climate. Ten years of data collected by Atmospheric Infrared Sounder (AIRS) allow us to identify decadal trends in frequency of occurrence of DCCs over land and ocean. In the past, DCCs have been identified in the thermal infrared by three methods: (1) thresholds based on the absolute value of an atmospheric window channel brightness temperature; (2) thresholds based on the difference between the brightness temperature in an atmospheric window channel and the brightness temperature centered on a strong water vapor absorption line; and (3) a threshold using the difference between the window channel brightness temperature and the tropopause temperature based on climatology. Simultaneous observations of these infrared identified DCCs with the Advanced Microwave Sounding Unit–Humidity Sounder for Brazil (AMSU-HSB) using 183 GHz water channels provide a statistical correlation with microwave deep convection and overshooting convection. In the past 10 years, the frequency of occurrence of DCCs has decreased for the tropical ocean, while it has increased for tropical land. The area of the tropical zone associated with DCCs is typically much less than 1%. We find that the least frequent, more extreme DCCs show the largest trend in frequency of occurrence, increasing over land and decreasing over ocean. The trends for land and ocean closely balance, such that the DCC frequency changed at an insignificant rate for the entire tropical zone. This pattern of essentially zero trend for the tropical zone, but opposite land/ocean trends, is consistent with measurements of global precipitation. The changes in frequency of occurrence of the DCCs are correlated with the Niño34 index, which defines the sea surface temperature (SST) anomaly in the east-central Pacific. This is also consistent with patterns seen in global precipitation. This suggests that the observed changes in the frequency are part of a decadal variability characterized by shifts in the main tropical circulation patterns, which does not fully balance in the 10-year AIRS data record. The regional correlations and anti-correlations of the DCC frequency anomaly with the Multivariate ENSO Index (MEI) provide a new perspective for the regional analysis of past events, since the SST anomaly in the Nino34 region is available in the form of the extended MEI from 1871.

scholarly journals Frequency of deep convective clouds in the tropical zone from ten years of AIRS data

2013 ◽  
Vol 13 (4) ◽  
pp. 10009-10047
Author(s):  
H. H. Aumann ◽  
A. Ruzmaikin
Keyword(s):  
Water Vapor ◽  
Brightness Temperature ◽  
Frequency Of Occurrence ◽  
Tropical Zone ◽  
Convective Clouds ◽  
Atmospheric Window ◽  
Deep Convective Clouds ◽  
Sst Anomaly ◽  
The Difference ◽  
Global Precipitation

Abstract. Deep Convective Clouds (DCC) have been widely studied because of their association with heavy precipitation and severe weather events. To identify DCC with Atmospheric Infrared Sounder (AIRS) data we use three types of thresholds: (1) thresholds based on the absolute value of an atmospheric window channel brightness temperature; (2) thresholds based on the difference between the brightness temperature in an atmospheric window channel and the brightness temperature centered on a strong water vapor absorption line; and (3) a threshold using the difference between the window channel brightness temperature and the tropopause temperature based on climatology. We find that DCC identified with threshold (2) (referred to as DCCw4) cover 0.16% of the area of the tropical zone and 72% of them are identified as deep convective, 39% are overshooting based on simultaneous observations with the Advanced Microwave Sounding Unit-HSB (AMSU-HSB) 183 GHz water vapor channels. In the past ten years the frequency of occurrence of DCC decreased for the tropical ocean, while it increased for tropical land. The land increase-ocean decrease closely balance, such that the DCC frequency changed at an insignificant rate for the entire tropical zone. This pattern of essentially zero trend for the tropical zone, but opposite land/ocean trends, is consistent with measurements of global precipitation. The changes in frequency of occurrence of the DCC are correlated with the Niño34 index, which defines the SST anomaly in the East-Central Pacific. This is also consistent with patterns seen in global precipitation. This suggests that the observed changes in the frequency are part of a decadal variability characterized by shifts in the main tropical circulation patterns, which does not fully balance in the ten year AIRS data record. The regional correlations and anti-correlations of the DCC frequency anomaly with the Multivariate ENSO Index (MEI) provides a new perspective for the regional analysis of past events, since the SST anomaly in the Nino34 region is available in the form of the extended MEI since 1871. Depending on the selected threshold, the frequency of DCC in the tropical zone ranges from 0.06% to 0.8% of the area. We find that the least frequent, more extreme DCC also show the largest trend in frequency, increasing over land, decreasing over ocean. This finding fits into the framework of how weather extremes respond to climate change.

scholarly journals Trends of MSU Brightness Temperature in the Middle Troposphere Simulated by CMIP5 Models and Their Sensitivity to Cloud Liquid Water

2015 ◽  
Vol 32 (5) ◽  
pp. 1029-1041
Author(s):  
Xuanze Zhang ◽  
Xiaogu Zheng ◽  
Zhian Sun ◽  
San Luo
Keyword(s):  
Brightness Temperature ◽  
Liquid Water ◽  
Weighting Function ◽  
Atmospheric Temperature ◽  
Temperature Trend ◽  
Cmip5 Models ◽  
Transfer Model ◽  
Weighting Functions ◽  
Cloud Liquid Water ◽  
Middle Troposphere

AbstractOnly a climate model that is able to simulate well the historical atmospheric temperature trend can be used for estimating the future atmospheric temperature trends on different emission scenarios. Satellite-based Microwave Sounding Unit (MSU) brightness temperature in the middle troposphere (T2) is an important analog of midtropospheric atmospheric temperature. So, there is the need to compare the atmospheric temperature trend simulated by the fifth phase of the Coupled Model Intercomparison Project (CMIP5) historical realizations and the observed MSU T2. There are two approaches for estimating modeled MSU T2: apply a global-mean static weighting function to generate the weighted average of the modeled temperature at all atmospheric layers and simulate satellite-view MSU T2 using the model’s output as input into a radiative transfer model (RTM).In this paper, the two approaches for estimating modeled MSU T2 are evaluated. For each CMIP5, it is shown that there exists a model-simulated static weighting function, such that the MSU T2 trend using the weighting function is equivalent to that calculated by RTM. The effect of modeled cloud liquid water on MSU T2 trends in CMIP5 simulations is investigated by comparing the modeled cloud liquid water vertical profile and the weighting function. Moreover, it is found that warming trends of MSU T2 for CMIP5 simulations calculated by the RTM are about 15% less than those using the two traditional static weighting functions. By comparing the model-derived weighting function with the two traditional weighting functions, the reason for the systematical biases is revealed.

scholarly journals Introducing Hysteresis in Snow Depletion Curves to Improve the Water Budget of a Land Surface Model in an Alpine Catchment

2014 ◽  
Vol 15 (2) ◽  
pp. 631-649 ◽  
Author(s):  
Claire Magand ◽  
Agnès Ducharne ◽  
Nicolas Le Moine ◽  
Simon Gascoin
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Water Budget ◽  
Land Surface Model ◽  
Surface Model ◽  
Depletion Curve ◽  
Physically Based ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference ◽  
Snow Model

Abstract The Durance watershed (14 000 km2), located in the French Alps, generates 10% of French hydropower and provides drinking water to 3 million people. The Catchment land surface model (CLSM), a distributed land surface model (LSM) with a multilayer, physically based snow model, has been applied in the upstream part of this watershed, where snowfall accounts for 50% of the precipitation. The CLSM subdivides the upper Durance watershed, where elevations range from 800 to 4000 m within 3580 km2, into elementary catchments with an average area of 500 km2. The authors first show the difference between the dynamics of the accumulation and ablation of the snow cover using Moderate Resolution Imaging Spectroradiometer (MODIS) images and snow-depth measurements. The extent of snow cover increases faster during accumulation than during ablation because melting occurs at preferential locations. This difference corresponds to the presence of a hysteresis in the snow-cover depletion curve of these catchments, and the CLSM was adapted by implementing such a hysteresis in the snow-cover depletion curve of the model. Different simulations were performed to assess the influence of the parameterizations on the water budget and the evolution of the extent of the snow cover. Using six gauging stations, the authors demonstrate that introducing a hysteresis in the snow-cover depletion curve improves melting dynamics. They conclude that their adaptation of the CLSM contributes to a better representation of snowpack dynamics in an LSM that enables mountainous catchments to be modeled for impact studies such as those of climate change.

scholarly journals Assessment of the calibration performance of satellite visible channels using cloud targets: application to Meteosat-8/9 and MTSAT-1R

2010 ◽  
Vol 10 (5) ◽  
pp. 12629-12664 ◽  
Author(s):  
S.-H. Ham ◽  
B. J. Sohn
Keyword(s):  
Three Dimensional ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Perfect Agreement ◽  
Convective Clouds ◽  
Calibration Methods ◽  
Matching Technique ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. To examine the calibration performance of the Meteosat-8/9 Spinning Enhanced Visible Infra-Red Imager (SEVIRI) 0.640-μm and the Multi-functional Transport Satellite (MTSAT)-1R 0.724-μm channels, three calibration methods were employed. First, a ray-matching technique was used to compare Meteosat-8/9 and MTSAT-1R visible channel reflectances with the well-calibrated Moderate Resolution Imaging Spectroradiometer (MODIS) 0.646-μm channel reflectances. Spectral differences of the response function between the two channels of interest were taken into account for the comparison. Second, collocated MODIS cloud products were used as inputs to a radiative transfer model to calculate Meteosat-8/9 and MTSAT-1R visible channel reflectances. In the simulation, the three-dimensional radiative effect of clouds was taken into account and was subtracted from the simulated reflectance to remove the simulation bias caused by the plane-parallel assumption. Third, an independent method used the typical optical properties of deep convective clouds (DCCs) to simulate reflectances of selected DCC targets. Although the three methods were not in perfect agreement, the results suggest that calibration accuracies were within 5–10% for the Meteosat-8 0.640-μm channel, 4–9% for the Meteosat-9 0.640-μm channel, and up to 20% for the MTSAT-1R 0.724-μm channel. The results further suggest that the solar channel calibration scheme combining the three methods in this paper can be used as a tool to monitor the calibration performance of visible sensors that are particularly not equipped with an onboard calibration system.

scholarly journals Evaluation and Improvement of Turbulence Parameterization inside Deep Convective Clouds at Kilometer-Scale Resolution

2017 ◽  
Vol 145 (10) ◽  
pp. 3947-3967 ◽  
Author(s):  
Antoine Verrelle ◽  
Didier Ricard ◽  
Christine Lac
Keyword(s):  
Thermal Effects ◽  
Convective Cloud ◽  
Coarse Graining ◽  
Eddy Diffusivity ◽  
Convective Clouds ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Deep Convective Clouds ◽  
The Difference ◽  
Horizontal Grid

A challenge for cloud-resolving models is to make subgrid schemes suitable for deep convective clouds. A benchmark large-eddy simulation (LES) was conducted on a deep convective cloud with 50-m grid spacing. The reference turbulence fields for horizontal grid spacings of 500 m, 1 km, and 2 km were deduced by coarse graining the 50-m LES outputs, allowing subgrid fields to be characterized. The highest values of reference subgrid turbulent kinetic energy (TKE) were localized in the updraft core, and the production of subgrid TKE was dominated by thermal effects at coarser resolution (2 and 1 km) and by dynamical effects at finer resolution than 500 m. Countergradient areas due to nonlocal mixing appeared on the subgrid vertical thermodynamical fluxes in the updraft core and near the cloud top. The subgrid dynamical variances were anisotropic but the difference between vertical and horizontal variances diminished with increasing resolution. Then offline and online evaluations were conducted for this deep convective case with two different parameterization approaches at kilometer-scale resolution and gave the same results. A commonly used eddy-diffusivity turbulence scheme underestimated the thermal production of subgrid TKE and did not enable the countergradient structures to be reproduced. In contrast, the approach proposed by Moeng, parameterizing the subgrid vertical thermodynamical fluxes in terms of horizontal gradients of resolved variables, reproduced these characteristics and limited the overestimation of vertical velocity.

scholarly journals Retrieval of tropospheric CO column from hyperspectral infrared sounders – application to four years of Aqua/AIRS and MetOp-A/IASI

2012 ◽  
Vol 5 (10) ◽  
pp. 2413-2429 ◽  
Author(s):  
T. Thonat ◽  
C. Crevoisier ◽  
N. A. Scott ◽  
A. Chédin ◽  
T. Schuck ◽  
...  
Keyword(s):  
Weighting Function ◽  
Signal To Noise Ratio ◽  
Surface Characteristics ◽  
Atlantic Multidecadal Oscillation ◽  
Relative Difference ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Tropical Regions ◽  
Brightness Temperatures ◽  
The Difference

Abstract. Four years of tropospheric integrated content of CO were retrieved from infrared hyperspectral observations of AIRS onboard Aqua and IASI onboard MetOp-A, for the period July 2007–June 2011. The retrieval method is based on a double differential approach that relies on the difference between brightness temperatures observed by the sounder and BT simulated by the Automatised Atmospheric Absorption Atlas (4A) radiative transfer model on colocated ECMWF reanalyses, for several couples of channels located in the 4.67 μm CO band. AIRS and IASI give access to similar integrated contents of CO with a maximum sensitivity near 450 hPa and a half-height width of the weighting function between 200 and 750 hPa depending on the thermal contrast (i.e., the difference between the surface temperature and the temperature of the first pressure level). However, differences in their spectral and radiometric characteristics yield differences in the retrieval characteristics with AIRS selected couples of channels being more sensitive to surface characteristics. Moreover, IASI covers the whole CO absorption band, with a 3 times better spectral resolution, giving access to channels presenting a 3 times higher signal to noise ratio. This results in a better precision and lower standard deviation of the IASI retrievals. Conservatively, comparisons with CARIBIC aircraft measurements yield an averaged relative difference of 3.4% for IASI and 4.9% for AIRS. On average, AIRS and IASI retrievals are in very good agreement, showing the same seasonality, seasonal amplitudes, interannual variability and spatial distribution. The analysis of the monthly evolution of CO particularly highlights the expected strong influence of biomass burning on the evolution of CO in several tropical regions. In particular, a sharp increase in CO in 2010 in the southern tropics, especially over South America and South Africa, is observed, and is shown to be related to El Niño and to the Atlantic Multidecadal Oscillation.

scholarly journals Bi-Spectral Infrared Algorithm for Cloud Coverage over Oceans by the JEM-EUSO Mission Program

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6506
Author(s):  
David Santalices ◽  
Susana Briz ◽  
Antonio J. de Castro ◽  
Fernando López
Keyword(s):  
Brightness Temperature ◽  
Ad Hoc ◽  
Low Cost ◽  
Infrared Camera ◽  
Cosmic Ray ◽  
High Energy ◽  
Ir Camera ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference ◽  
Split Window Algorithm

The need to monitor specific areas for different applications requires high spatial and temporal resolution. This need has led to the proliferation of ad hoc systems on board nanosatellites, drones, etc. These systems require low cost, low power consumption, and low weight. The work we present follows this trend. Specifically, this article evaluates a method to determine the cloud map from the images provided by a simple bi-spectral infrared camera within the framework of JEM-EUSO (The Joint Experiment Missions-Extrem Universe Space Observatory). This program involves different experiments whose aim is determining properties of Ultra-High Energy Cosmic Ray (UHECR) via the detection of atmospheric fluorescence light. Since some of those projects use UV instruments on board space platforms, they require knowledge of the cloudiness state in the FoV of the instrument. For that reason, some systems will include an infrared (IR) camera. This study presents a test to generate a binary cloudiness mask (CM) over the ocean, employing bi-spectral IR data. The database is created from Moderate-Resolution Imaging Spectroradiometer (MODIS) data (bands 31 and 32). The CM is based on a split-window algorithm. It uses an estimation of the brightness temperature calculated from a statistical study of an IR images database along with an ancillary sea surface temperature. This statistical procedure to obtain the estimate of the brightness temperature is one of the novel contributions of this work. The difference between the measured and estimation of the brightness temperature determines whether a pixel is cover or clear. That classification requires defining several thresholds which depend on the scenarios. The procedure for determining those thresholds is also novel. Then, the results of the algorithm are compared with the MODIS CM. The agreement is above 90%. The performance of the proposed CM is similar to that of other studies. The validation also shows that cloud edges concentrate the vast majority of discrepancies with the MODIS CM. The relatively high accuracy of the algorithm is a relevant result for the JEM-EUSO program. Further work will combine the proposed algorithm with complementary studies in the framework of JEM-EUSO to reinforce the CM above the cloud edges.

scholarly journals Assessment of the calibration performance of satellite visible channels using cloud targets: application to Meteosat-8/9 and MTSAT-1R

2010 ◽  
Vol 10 (22) ◽  
pp. 11131-11149 ◽  
Author(s):  
S.-H. Ham ◽  
B. J. Sohn
Keyword(s):  
Three Dimensional ◽  
Calibration Coefficient ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Perfect Agreement ◽  
Convective Clouds ◽  
Calibration Methods ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. To examine the calibration performance of the Meteosat-8/9 Spinning Enhanced Visible Infra-Red Imager (SEVIRI) 0.640-μm and the Multi-functional Transport Satellite (MTSAT)-1R 0.724-μm channels, three calibration methods are employed. Total eight months during the 2004–2007 period are used for SEVIRI, and total seven months during the 2007–2008 period are used for MTSAT-1R. First, a ray-matching technique is used to compare Meteosat-8/9 and MTSAT-1R visible channel reflectances with the well-calibrated Moderate Resolution Imaging Spectroradiometer (MODIS) 0.646-μm channel reflectances. Spectral differences of the response function between the two channels of interest are taken into account for the comparison. Second, collocated MODIS cloud products are used as inputs to a radiative transfer model (RTM) to calculate Meteosat-8/9 and MTSAT-1R visible channel reflectances. In the simulation, cloud three-dimensional (3-D) radiative effect associated with subgrid variations is taken into account using the lognormal-independent column approximation (LN-ICA) to minimize the simulation bias caused by the plane-parallel homogeneous assumption. Third, an independent method uses the typical optical properties of deep convective clouds (DCCs) to simulate reflectances of selected DCC targets. Although all three methods are not in perfect agreement, the results suggest that calibration coefficients of Meteosat-8/9 0.640-μm channels are underestimated by 6–7%. On the other hand, the calibration accuracy of MTSAT-1R visible channel appears to be variable with the target reflectance itself because of an underestimate of calibration coefficient (up to 20%) and a non-zero space offset. The results further suggest that the solar channel calibration scheme combining the three methods in this paper can be used as a tool to monitor the calibration performance of visible sensors that are particularly not equipped with an onboard calibration system.

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