scholarly journals Assignment of rainfall confidence values using multispectral satellite data at mid-latitudes: first results

2007 ◽  
Vol 10 ◽  
pp. 99-102 ◽  
Author(s):  
T. Nauss ◽  
A. A. Kokhanovsky
Keyword(s):  
Satellite Data ◽  
Liquid Water ◽  
Regression Function ◽  
Radar Data ◽  
New Method ◽  
Droplet Radius ◽  
Liquid Water Path ◽  
Water Path ◽  
Concept Model ◽  
Cloud Properties

Abstract. The authors propose a new method for the assignment of rainfall confidences on a pixel basis using cloud properties derived from optical satellite data during daytime. This approach is based on the concept model that the probability for precipitation is a function of the liquid water path, which in turn can be computed using the satellite-retrieved cloud optical thickness and the cloud effective droplet radius. In order to evaluate the principal potential of this idea, scenes from the Terra-MODIS sensor during the severe European summer floods in 2002 have been analysed in order to derive a corresponding regression function that interlinks the liquid water path with the rainfall probability or better with the confidence that a pixel which is classified as raining does actually rain. A first evaluation against ground-based radar data during March 2004 shows good skill of this new method.

scholarly journals Estimation of Liquid Cloud Properties that Conserve Total-Scene Reflectance Using Satellite Measurements

2011 ◽  
Vol 50 (1) ◽  
pp. 96-109 ◽  
Author(s):  
Michael J. Foster ◽  
Ralf Bennartz ◽  
Andrew Heidinger
Keyword(s):  
Liquid Water ◽  
New Method ◽  
Atmospheric Conditions ◽  
Liquid Water Path ◽  
Satellite Measurements ◽  
Water Path ◽  
Cloud Properties ◽  
Visible Reflectance ◽  
Very High

Abstract A new method of deriving statistical moments related to the distribution of liquid water path over partially cloudy scenes is tested using a satellite cloud climatology. The method improves the ability to reconstruct total-scene visible reflectance when compared with an approach that relies on valid liquid water path retrievals, and thus it maintains physical consistency with the primary satellite observations when deriving cloud climatologies. A global application of the new method finds a mean bias of −0.008 ± 0.017 when reconstructing total-scene reflectance from liquid water path distributions, as compared with a bias of 0.05 ± 0.047 when using a conventional approach. Application of the method to a multidecadal cloud climatology suggests that this may provide a means of identifying data artifacts that could affect long-term cloud property trends. The conservation of reflectance plus the ease of applicability to various satellite datasets makes this method a valuable tool for model validation and comparison of satellite climatologies. Gaussian and gamma functions are used to approximate the distribution of horizontal subgrid-scale liquid water path for 1° × 1° scenes, and while both functions perform well for the majority of atmospheric conditions, it is found that the Gaussian distribution generates a negative bias for cases in which visible reflectance is very high and that neither function is able to represent liquid water path well in the few cases in which the observed distribution is bi- or multimodal.

scholarly journals How does the UKESM1 climate model produce its cloud-aerosol forcing in the North Atlantic?

2020 ◽  
Author(s):  
Daniel P. Grosvenor ◽  
Kenneth S. Carslaw
Keyword(s):  
Spatial Pattern ◽  
North Atlantic ◽  
Liquid Water ◽  
Liquid Water Path ◽  
Water Path ◽  
The North ◽  
Aerosol Forcing ◽  
Cloud Properties ◽  
The North Atlantic ◽  
Low Altitude

Abstract. Climate variability in the North Atlantic influences processes such as hurricane activity and droughts. Global model simulations have identified aerosol-cloud interactions (ACIs) as an important driver of sea surface temperature variability via surface aerosol forcing. However, ACIs are a major cause of uncertainty in climate forcing, therefore caution is needed in interpreting the results from coarse resolution, highly parameterized global models. Here we separate and quantify the components of the surface shortwave effective radiative forcing (ERF) due to aerosol in the atmosphere-only version of the UK Earth System Model (UKESM1) and evaluate the cloud properties and their radiative effects against observations. We focus on a northern region of the North Atlantic (NA) where stratocumulus clouds dominate (denoted the northern NA region) and a southern region where trade cumulus and broken stratocumlus dominate (southern NA region). Aerosol forcing was diagnosed using a pair of simulations in which the meteorology is approximately fixed via nudging to analysis; one simulation has pre-industrial (PI) and one has present-day (PD) aerosol emissions. Contributions to the surface ERF from changes in cloud fraction (fc), in-cloud liquid water path (LWPic) and droplet number concentration (Nd) were quantified. Over the northern NA region increases in Nd and LWPic dominate the forcing. This is likely because the high fc there precludes further large increases in fc and allows cloud brightening to act over a larger region. Over the southern NA region increases in fc dominate due to the suppression of rain by the additional aerosols. Aerosol-driven increases in macrophysical cloud properties (LWPic and fc) will rely on the response of the boundary layer parameterization, along with input from the cloud microphysics scheme, which are highly uncertain processes. Model gridboxes with low-altitude clouds present in both the PI and PD dominate the forcing in both regions. In the northern NA the brightening of completely overcast low cloud scenes (100 % cloud cover, likely stratocumlus) contributes the most, whereas in the southern NA the creation of clouds with fc of around 20 % from clear skies in the PI was the largest single contributor, suggesting that trade cumulus clouds are created in response to increases in aerosol. The creation of near-overcast clouds was also important there. The correct spatial pattern, coverage and properties of clouds are important for determining the magnitude of aerosol forcing so we also assess the realism of the modelled PD clouds against satellite observations. We find that the model reproduces the spatial pattern of all the observed cloud variables well, but that there are biases. The shortwave top-of-the-atmosphere (SWTOA) flux is overestimated by 5.8 % in the northern NA region and 1.7 % in the southern NA, which we attribute mainly to positive biases in low-altitude fc. Nd is too low by −20.6 % in the northern NA and too high by by 21.5 % in the southern NA, but does not contribute greatly to the main SWTOA biases. Cloudy-sky liquid water path mainly shows biases north of Scandinavia that reach up to between 50 and 100 % and dominate the SWTOA bias in that region. The large contribution to aerosol forcing in the UKESM1 model from highly uncertain macrophysical adjustments suggests that further targeted observations are needed to assess rain formation processes, how they depend on aerosols and the model response to precipitation in order to reduce uncertainty in climate projections.

scholarly journals Discriminating raining from non-raining clouds at mid-latitudes using multispectral satellite data

2006 ◽  
Vol 6 (12) ◽  
pp. 5031-5036 ◽  
Author(s):  
T. Nauss ◽  
A. A. Kokhanovsky
Keyword(s):  
Satellite Data ◽  
Cloud Droplet ◽  
Threshold Value ◽  
Convective Precipitation ◽  
Droplet Radius ◽  
Concept Model ◽  
Cloud Properties ◽  
Frontal Systems ◽  
Precipitating Clouds ◽  
Cloud Top Temperature

Abstract. We propose a new method for the delineation of precipitation using cloud properties derived from optical satellite data. This approach is not only sufficient for the detection of mainly convective precipitation by means of the commonly used connection between infrared cloud top temperature and rainfall probability but enables the detection of stratiform precipitation (e.g., in connection with mid-latitude frontal systems). The scheme presented is based on the concept model, that precipitating clouds must have both a sufficient vertical extent and large enough droplets. Therefore, we have analysed MODIS scenes during the severe European summer floods in 2002 and retrieved functions for the computation of an auto-adaptive threshold value of the effective cloud droplet radius with respect to the corresponding optical thickness which links these cloud properties with rainfall areas on a pixel basis.

scholarly journals Cloud<i>_</i>cci ATSR-2 and AATSR data set version 3: a 17-year climatology of global cloud and radiation properties

2020 ◽  
Vol 12 (3) ◽  
pp. 2121-2135
Author(s):  
Caroline A. Poulsen ◽  
Gregory R. McGarragh ◽  
Gareth E. Thomas ◽  
Martin Stengel ◽  
Matthew W. Christensen ◽  
...  
Keyword(s):  
Liquid Water ◽  
European Space Agency ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Liquid Water Path ◽  
Data Set ◽  
Water Path ◽  
Cloud Properties ◽  
Wide Range ◽  
Good Agreement

Abstract. We present version 3 (V3) of the Cloud_cci Along-Track Scanning Radiometer (ATSR) and Advanced ATSR (AATSR) data set. The data set was created for the European Space Agency (ESA) Cloud_cci (Climate Change Initiative) programme. The cloud properties were retrieved from the second ATSR (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) spanning 1995–2003 and the AATSR on board Envisat, which spanned 2002–2012. The data are comprised of a comprehensive set of cloud properties: cloud top height, temperature, pressure, spectral albedo, cloud effective emissivity, effective radius, and optical thickness, alongside derived liquid and ice water path. Each retrieval is provided with its associated uncertainty. The cloud property retrievals are accompanied by high-resolution top- and bottom-of-atmosphere shortwave and longwave fluxes that have been derived from the retrieved cloud properties using a radiative transfer model. The fluxes were generated for all-sky and clear-sky conditions. V3 differs from the previous version 2 (V2) through development of the retrieval algorithm and attention to the consistency between the ATSR-2 and AATSR instruments. The cloud properties show improved accuracy in validation and better consistency between the two instruments, as demonstrated by a comparison of cloud mask and cloud height with co-located CALIPSO data. The cloud masking has improved significantly, particularly in its ability to detect clear pixels. The Kuiper Skill score has increased from 0.49 to 0.66. The cloud top height accuracy is relatively unchanged. The AATSR liquid water path was compared with the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) in regions of stratocumulus cloud and shown to have very good agreement and improved consistency between ATSR-2 and AATSR instruments. The correlation with MAC-LWP increased from 0.4 to over 0.8 for these cloud regions. The flux products are compared with NASA Clouds and the Earth's Radiant Energy System (CERES) data, showing good agreement within the uncertainty. The new data set is well suited to a wide range of climate applications, such as comparison with climate models, investigation of trends in cloud properties, understanding aerosol–cloud interactions, and providing contextual information for co-located ATSR-2/AATSR surface temperature and aerosol products. The following new digital identifier has been issued for the Cloud_cci ATSR-2/AATSRv3 data set: https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003 (Poulsen et al., 2019).

scholarly journals A dataset of microphysical cloud parameters, retrieved from Emission-FTIR spectra measured in Arctic summer 2017

2021 ◽  
Author(s):  
Philipp Richter ◽  
Mathias Palm ◽  
Christine Weinzierl ◽  
Hannes Griesche ◽  
Penny M. Rowe ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Infrared Spectra ◽  
Liquid Water ◽  
Microwave Radiometer ◽  
The Arctic ◽  
Liquid Water Path ◽  
Water Path ◽  
Cloud Parameters ◽  
Cloud Properties ◽  
Infrared Spectral

Abstract. A dataset of microphysical cloud parameters from optically thin clouds, retrieved from infrared spectral radiances measured in summer 2017 in the Arctic, is presented. Measurements were conducted using a mobile Fourier-transform infrared (FTIR) spectrometer which was carried by the RV Polarstern. This dataset contains retrieved optical depths and effective radii of ice and water, from which the liquid water path and ice water path are calculated. These water paths and the effective radii are compared with derived quantities from a combined cloud radar, lidar and microwave radiometer measurement synergy retrieval, called Cloudnet. Comparing the liquid water paths from the infrared retrieval and Cloudnet shows significant correlations with a standard deviation of 8.60 g · m−2. Although liquid water path retrievals from microwave radiometer data come with a uncertainty of at least 20 g · m−2, a significant correlation and a standard deviation of 5.32 g · m−2 between the results of clouds with a liquid water path of at most 20 g · m−2 retrieved from infrared spectra and results from Cloudnet can be seen. Therefore, despite its large uncertainty, the comparison with data retrieved from infrared spectra shows that optically thin clouds of the measurement campaign in summer 2017 can be observed well using microwave radiometers within the Cloudnet framework. Apart from this, the dataset of microphysical cloud properties presented here allows to perform calculations of the cloud radiative effects, when the Cloudnet data from the campaign are not available, which was from the 22nd July 2017 until the 19th August 2017. The dataset is published at Pangaea (Richter et al., 2021).

scholarly journals Scale-by-scale analysis of probability distributions for global MODIS-AQUA cloud properties: how the large scale signature of turbulence may impact statistical analyses of clouds

2011 ◽  
Vol 11 (6) ◽  
pp. 2893-2901 ◽  
Author(s):  
M. de la Torre Juárez ◽  
A. B. Davis ◽  
E. J. Fetzer
Keyword(s):  
Liquid Water ◽  
Large Scale ◽  
Cloud Fraction ◽  
Effective Radius ◽  
Distribution Functions ◽  
Liquid Water Path ◽  
Water Path ◽  
Cloud Properties ◽  
Standard Deviations ◽  
Log Normal

Abstract. Means, standard deviations, homogeneity parameters used in models based on their ratio, and the probability distribution functions (PDFs) of cloud properties from the MODerate resolution Infrared Spectrometer (MODIS) are estimated globally as function of averaging scale varying from 5 to 500 km. The properties – cloud fraction, droplet effective radius, and liquid water path – all matter for cloud-climate uncertainty quantification and reduction efforts. Global means and standard deviations are confirmed to change with scale. For the range of scales considered, global means vary only within 3% for cloud fraction, 7% for liquid water path, and 0.2% for cloud particle effective radius. These scale dependences contribute to the uncertainties in their global budgets. Scale dependence for standard deviations and generalized flatness are compared to predictions for turbulent systems. Analytical expressions are identified that fit best to each observed PDF. While the best analytical PDF fit to each variable differs, all PDFs are well described by log-normal PDFs when the mean is normalized by the standard deviation inside each averaging domain. Importantly, log-normal distributions yield significantly better fits to the observations than gaussians at all scales. This suggests a possible approach for both sub-grid and unified stochastic modeling of these variables at all scales. The results also highlight the need to establish an adequate spatial resolution for two-stream radiative studies of cloud-climate interactions.

scholarly journals Cloud_cci ATSR-2 and AATSR dataset version 3: a 17-yearclimatology of global cloud and radiation properties

2019 ◽  
Author(s):  
Caroline A. Poulsen ◽  
Gregory R. Mcgarragh ◽  
Gareth E. Thomas ◽  
Martin Stengel ◽  
Matthew W. Christiensen ◽  
...  
Keyword(s):  
Liquid Water ◽  
European Space Agency ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Liquid Water Path ◽  
Water Path ◽  
Cloud Properties ◽  
Wide Range ◽  
Initiative Program ◽  
Good Agreement

Abstract. We present version 3 (V3) of the Cloud_cci ATSR-2/AATSR dataset. The dataset was created for the European Space Agency (ESA) Cloud_cci (Climate Change Initiative) program. The cloud properties were retrieved from the second Along- Track Scanning Radiometer (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) spanning 1995–2003 and the Advanced ATSR (AATSR) on board Envisat, which spanned 2002–2012. The data comprises a comprehensive set of cloud properties: cloud top height, temperature, pressure, spectral albedo, cloud effective emissivity, effective radius and optical thickness alongside derived liquid and ice water path. Each retrieval is provided with its associated uncertainty. The cloud property retrievals are accompanied by high-resolution top and bottom-of-atmosphere short- and long-wave fluxes that have been derived from the retrieved cloud properties using a radiative transfer model. The fluxes were generated for all-sky and clear-sky conditions. V3 differs from the previous version 2 (V2) through development of the retrieval algorithm and attention to the consistency between the ATSR-2 and AATSR instruments. The cloud properties show improved accuracy in validation and better consistency between the two instruments, as demonstrated by a comparison of cloud mask and cloud height with collocated CALIPSO data. The cloud masking has improved significantly, particularly the ability to detect clear pixels The Kuiper Skill score has increased from .49 to .66. The cloud top height accuracy is relatively unchanged. The AATSR liquid water path was compared with the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) in regions of stratocumulous cloud and shown to have very good agreement and improved consistency between ATSR-2 and AATSR instruments, the Correlation with MAC-LWP increase from .4 to over .8 for these cloud regions. The flux products are compared with NASA Clouds and the Earth’s Radiant Energy System (CERES) data, showing good agreement within the uncertainty. The new dataset is well suited to a wide range of climate applications, such as comparison with climate models, investigation of trends in cloud properties, understanding aerosol-cloud interactions, and providing contextual information for collocated ATSR-2/AATSR surface temperature and aerosol products. For the Cloud_cci ATSR-2/AATSRv3 dataset a new digital identifier has been issued: https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003 Poulsen et al. (2019).

scholarly journals Discriminating raining from non-raining clouds at mid-latitudes using multispectral satellite data

2006 ◽  
Vol 6 (1) ◽  
pp. 1385-1398 ◽  
Author(s):  
T. Nauss ◽  
A. A. Kokhanovsky
Keyword(s):  
Satellite Data ◽  
Cloud Droplet ◽  
Threshold Value ◽  
Droplet Radius ◽  
Concept Model ◽  
Cloud Properties ◽  
Frontal Systems ◽  
Terra Modis ◽  
Precipitating Clouds ◽  
Cloud Top Temperature

Abstract. We propose a new method for the delineation of precipitation using cloud properties derived from optical satellite data. This approach is not only sufficient for the detection of mainly convective driven precipitation by means of the commonly used connection between infrared cloud-top temperature and rainfall probability but enables the detection of stratiform precipitation (e.g., in connection with mid-latitude frontal systems). The scheme presented is based on the concept model, that precipitating clouds must have both a large enough vertical extent and large enough droplets. Therefore, we have analyzed Terra-MODIS scenes during the severe European summer floods in 2002 and retrieved functions for the computation of an auto-adaptive threshold value of the effective cloud droplet radius with respect to the corresponding optical thickness which links these cloud properties with rainfall areas on a pixel basis.

scholarly journals Simulating Clouds with Global Climate Models: A Comparison of CMIP5 Results with CMIP3 and Satellite Data

2013 ◽  
Vol 26 (11) ◽  
pp. 3823-3845 ◽  
Author(s):  
Axel Lauer ◽  
Kevin Hamilton
Keyword(s):  
Interannual Variability ◽  
Liquid Water ◽  
Hydrological Cycle ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Liquid Water Path ◽  
Water Path ◽  
Cloud Properties ◽  
Intercomparison Project

Abstract Clouds are a key component of the climate system affecting radiative balances and the hydrological cycle. Previous studies from the Coupled Model Intercomparison Project phase 3 (CMIP3) showed quite large biases in the simulated cloud climatology affecting all GCMs as well as a remarkable degree of variation among the models that represented the state of the art circa 2005. Here the progress that has been made in recent years is measured by comparing mean cloud properties, interannual variability, and the climatological seasonal cycle from the CMIP5 models with satellite observations and with results from comparable CMIP3 experiments. The focus is on three climate-relevant cloud parameters: cloud amount, liquid water path, and cloud radiative forcing. The comparison shows that intermodel differences are still large in the Coupled Model Intercomparison Project phase 5 (CMIP5) simulations, and reveals some small improvements of particular cloud properties in some regions in the CMIP5 ensemble over CMIP3. In CMIP5 there is an improved agreement of the modeled interannual variability of liquid water path and of the modeled longwave cloud forcing over mid- and high-latitude oceans with observations. However, the differences in the simulated cloud climatology from CMIP3 and CMIP5 are generally small, and there is very little to no improvement apparent in the tropical and subtropical regions in CMIP5. Comparisons of the results from the coupled CMIP5 models with their atmosphere-only versions run with observed SSTs show remarkably similar biases in the simulated cloud climatologies. This suggests the treatments of subgrid-scale cloud and boundary layer processes are directly implicated in the poor performance of current GCMs in simulating realistic cloud fields.

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