scholarly journals Exploiting the sensitivity of two satellite cloud height retrievals to cloud vertical distribution

2015 ◽  
Vol 8 (3) ◽  
pp. 2623-2655
Author(s):  
C. K. Carbajal Henken ◽  
L. Doppler ◽  
R. Lindstrot ◽  
R. Preusker ◽  
J. Fischer
Keyword(s):  
Absorption Band ◽  
Vertical Distribution ◽  
Land Surface ◽  
Weather Prediction ◽  
Single Layer ◽  
Thermal Infrared ◽  
Vertical Extent ◽  
Cloud Height ◽  
The Difference ◽  
The Impact

Abstract. This work presents a study on the sensitivity of two satellite cloud height retrievals to cloud vertical distribution. The difference in sensitivity is exploited by relating the difference in the retrieved cloud heights to cloud vertical extent. The two cloud height retrievals, performed within the Freie Universität Berlin AATSR MERIS Cloud (FAME-C) algorithm, are based on independent measurements and different retrieval techniques. First, cloud top temperature (CTT) is retrieved from Advanced Along Track Scanning Radiometer (AATSR) measurements in the thermal infrared. Second, cloud top pressure (CTP) is retrieved from Medium Resolution Imaging Spectrometer (MERIS) measurements in the oxygen-A absorption band. Both CTT and CTP are converted to cloud top height (CTH) using atmospheric profiles from a numerical weather prediction model. A sensitivity study using radiative transfer simulations in the near-infrared and thermal infrared were performed to demonstrate the larger impact of the assumed cloud vertical extinction profile on MERIS than on AATSR top-of-atmosphere measurements. The difference in retrieved CTH (ΔCTH) from AATSR and MERIS are related to cloud vertical extent (CVE) as observed by ground-based lidar and radar at three ARM sites. To increase the impact of the cloud vertical extinction profile on the MERIS-CTP retrievals, single-layer and geometrically thin clouds are assumed in the forward model. The results of the comparison to the ground-based observations were separated into single-layer and multi-layer cloud cases. Analogous to previous findings, the MERIS-CTP retrievals appear to be close to pressure levels in the middle of the cloud. Assuming a linear relationship, the ΔCTH multiplied by 2.5 gives an estimate on the CVE for single-layer clouds. The relationship is weaker for multi-layer clouds. Due to large variations of cloud vertical extinction profiles occurring in nature, a quantitative estimate of the cloud vertical extent is accompanied with large uncertainties. Yet, estimates of the CVE can contribute to the characterization of a cloudy scene. To demonstrate the plausibility of the approach, an estimate of the CVE was applied to a case study. In light of the follow-up mission Sentinel-3 with AATSR and MERIS like instruments, Sea and Land Surface Temperature Radiometer (SLSTR) and (Ocean and Land Colour Instrument) OLCI, respectively, for which the FAME-C algorithm can be easily adapted, a more accurate estimate of the CVE can be expected. OLCI will have three channels in the oxygen-A absorption band, thus providing more pieces of information on the cloud vertical extinction profile.

scholarly journals Exploiting the sensitivity of two satellite cloud height retrievals to cloud vertical distribution

2015 ◽  
Vol 8 (8) ◽  
pp. 3419-3431 ◽  
Author(s):  
C. K. Carbajal Henken ◽  
L. Doppler ◽  
R. Lindstrot ◽  
R. Preusker ◽  
J. Fischer
Keyword(s):  
Absorption Band ◽  
Vertical Distribution ◽  
Weather Prediction ◽  
Single Layer ◽  
Thermal Infrared ◽  
Additional Parameter ◽  
Vertical Extent ◽  
Cloud Height ◽  
The Difference ◽  
The Impact

Abstract. This work presents a study on the sensitivity of two satellite cloud height retrievals to cloud vertical distribution. The difference in sensitivity is exploited by relating the difference in the retrieved cloud heights to cloud vertical extent. The two cloud height retrievals, performed within the Freie Universität Berlin AATSR MERIS Cloud (FAME-C) algorithm, are based on independent measurements and different retrieval techniques. First, cloud-top temperature (CTT) is retrieved from Advanced Along Track Scanning Radiometer (AATSR) measurements in the thermal infrared. Second, cloud-top pressure (CTP) is retrieved from Medium Resolution Imaging Spectrometer (MERIS) measurements in the oxygen-A absorption band and a nearby window channel. Both CTT and CTP are converted to cloud-top height (CTH) using atmospheric profiles from a numerical weather prediction model. First, a sensitivity study using radiative transfer simulations in the near-infrared and thermal infrared was performed to demonstrate, in a quantitative manner, the larger impact of the assumed cloud vertical extinction profile, described in terms of shape and vertical extent, on MERIS than on AATSR top-of-atmosphere measurements. Consequently, cloud vertical extinction profiles will have a larger influence on the MERIS than on the AATSR cloud height retrievals for most cloud types. Second, the difference in retrieved CTH (ΔCTH) from AATSR and MERIS are related to cloud vertical extent (CVE), as observed by ground-based lidar and radar at three ARM sites. To increase the impact of the cloud vertical extinction profile on the MERIS-CTP retrievals, single-layer and geometrically thin clouds are assumed in the forward model. Similarly to previous findings, the MERIS-CTP retrievals appear to be close to pressure levels in the middle of the cloud. Assuming a linear relationship, the ΔCTH multiplied by 2.5 gives an estimate on the CVE for single-layer clouds. The relationship is stronger for single-layer clouds than for multi-layer clouds. Due to large variations of cloud vertical extinction profiles occurring in nature, a quantitative estimate of the cloud vertical extent is accompanied with large uncertainties. Yet, estimates of the CVE provide an additional parameter, next to CTH, that can be obtained from passive imager measurements and can be used to further describe cloud vertical distribution, thus contributing to the characterization of a cloudy scene. To further demonstrate the plausibility of the approach, an estimate of the CVE was applied to a case study. In light of the follow-up mission Sentinel-3 with AATSR and MERIS like instruments, Sea and Land Surface Temperature Radiometer (SLSTR) and (Ocean and Land Colour Instrument) OLCI, respectively, for which the FAME-C algorithm can be easily adapted, a more accurate estimate of the CVE can be expected. OLCI will have three channels in the oxygen-A absorption band, possibly providing enhanced information on cloud vertical distributions.

scholarly journals High-resolution fully-coupled atmospheric–hydrological modeling: a cross-compartment regional water and energy cycle evaluation

2020 ◽  
Author(s):  
Benjamin Fersch ◽  
Alfonso Senatore ◽  
Bianca Adler ◽  
Joël Arnault ◽  
Matthias Mauder ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Land Surface ◽  
Hydrological Modeling ◽  
Weather Prediction ◽  
Surface Model ◽  
Near Surface ◽  
Ground Heat Flux ◽  
The Impact ◽  
Fully Coupled ◽  
Regional Water

<p>The land surface and the atmospheric boundary layer are closely intertwined with respect to the exchange of water, trace gases and energy. Nonlinear feedback and scale dependent mechanisms are obvious by observations and theories. Modeling instead is often narrowed to single compartments of the terrestrial system or bound to traditional viewpoints of definite scientific disciplines. Coupled terrestrial hydrometeorological modeling systems attempt to overcome these limitations to achieve a better integration of the processes relevant for regional climate studies and local area weather prediction. We examine the ability of the hydrologically enhanced version of the Weather Research and Forecasting Model (WRF-Hydro) to reproduce the regional water cycle by means of a two-way coupled approach and assess the impact of hydrological coupling with respect to a traditional regional atmospheric model setting. It includes the observation-based calibration of the hydrological model component (offline WRF-Hydro) and a comparison of the classic WRF and the fully coupled WRF-Hydro models both with identical calibrated parameter settings for the land surface model (Noah-MP). The simulations are evaluated based on extensive observations at the pre-Alpine Terrestrial Environmental Observatory (TERENO Pre-Alpine) for the Ammer (600 km²) and Rott (55 km²) river catchments in southern Germany, covering a five month period (Jun–Oct 2016).</p><p>The sensitivity of 7 land surface parameters is tested using the <em>Latin-Hypercube One-factor-At-a-Time</em> (LH-OAT) method and 6 sensitive parameters are subsequently optimized for 6 different subcatchments, using the Model-Independent <em>Parameter Estimation and Uncertainty Analysis software</em> (PEST).</p><p>The calibration of the offline WRF-Hydro leads to Nash-Sutcliffe efficiencies between 0.56 and 0.64 and volumetric efficiencies between 0.46 and 0.81 for the six subcatchments. The comparison of classic WRF and fully coupled WRF-Hydro shows only tiny alterations for radiation and precipitation but considerable changes for moisture- and energy fluxes. By comparison with TERENO Pre-Alpine observations, the fully coupled model slightly outperforms the classic WRF with respect to evapotranspiration, sensible and ground heat flux, near surface mixing ratio, temperature, and boundary layer profiles of air temperature. The subcatchment-based water budgets show uniformly directed variations for evapotranspiration, infiltration excess and percolation whereas soil moisture and precipitation change randomly.</p>

scholarly journals The Impact of Initial Snow Conditions on the Numerical Weather Simulation of a Northern Rockies Atmospheric River

2021 ◽  
Vol 22 (1) ◽  
pp. 155-167
Author(s):  
William Rudisill ◽  
Alejandro Flores ◽  
James McNamara
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Weather Prediction ◽  
Hydrologic Model ◽  
Radiative Properties ◽  
Numerical Weather ◽  
Atmospheric River ◽  
Surface Snow ◽  
Snow Conditions ◽  
The Impact

AbstractSnow’s thermal and radiative properties strongly impact the land surface energy balance and thus the atmosphere above it. Land surface snow information is poorly known in mountainous regions. Few studies have examined the impact of initial land surface snow conditions in high-resolution, convection-permitting numerical weather prediction models during the midlatitude cool season. The extent to which land surface snow influences atmospheric energy transport and subsequent surface meteorological states is tested using a high-resolution (1 km) configuration of the Weather Research and Forecasting (WRF) Model, for both calm conditions and weather characteristic of a warm late March atmospheric river. A set of synthetic but realistic snow states are used as initial conditions for the model runs and the resulting differences are compared. We find that the presence (absence) of snow decreases (increases) 2-m air temperatures by as much as 4 K during both periods, and that the atmosphere responds to snow perturbations through advection of moist static energy from neighboring regions. Snow mass and snow-covered area are both important variables that influence 2-m air temperature. Finally, the meteorological states produced from the WRF experiments are used to force an offline hydrologic model, demonstrating that snowmelt rates can increase/decrease by factor of 2 depending on the initial snow conditions used in the parent weather model. We propose that more realistic representations of land surface snow properties in mesoscale models may be a source of hydrometeorological predictability

scholarly journals Impact of cirrus clouds heterogeneities on top-of-atmosphere thermal infrared radiation

2014 ◽  
Vol 14 (11) ◽  
pp. 5599-5615 ◽  
Author(s):  
T. Fauchez ◽  
C. Cornet ◽  
F Szczap ◽  
P. Dubuisson ◽  
T. Rosambert
Keyword(s):  
Radiative Transfer ◽  
Monte Carlo Model ◽  
Thermal Infrared ◽  
Brightness Temperatures ◽  
Spectral Bands ◽  
Thickness Standard ◽  
The Difference ◽  
Scale Properties ◽  
Parallel Approximation ◽  
The Impact

Abstract. This paper presents a study of the impact of cirrus cloud heterogeneities on the thermal infrared brightness temperatures at the top of the atmosphere (TOA). Realistic 3-D cirri are generated by a cloud generator based on simplified thermodynamic and dynamic equations and on the control of invariant scale properties. The 3-D thermal infrared radiative transfer is simulated with a Monte Carlo model for three typical spectral bands in the infrared atmospheric window. Comparisons of TOA brightness temperatures resulting from 1-D and 3-D radiative transfer show significant differences for optically thick cirrus (τ > 0.3 at 532 nm) and are mainly due to the plane-parallel approximation (PPA). At the spatial resolution of 1 km × 1 km, two principal parameters control the heterogeneity effects on brightness temperatures: i) the optical thickness standard deviation inside the observation pixel, ii) the brightness temperature contrast between the top of the cirrus~and the clear-sky atmosphere. Furthermore, we show that the difference between 1-D and 3-D brightness temperatures increases with the zenith view angle from two to ten times between 0° and 60° due to the tilted independent pixel approximation (TIPA).

The impact of London on a low-level jet

2021 ◽  
Author(s):  
Aristofanis Tsiringakis ◽  
Natalie Theeuwes ◽  
Janet Barlow ◽  
Gert-Jan Steeneveld
Keyword(s):  
Urban Area ◽  
Prediction Models ◽  
Weather Prediction ◽  
Vertical Mixing ◽  
Forecasting Model ◽  
Low Level ◽  
Low Level Jet ◽  
The Difference ◽  
The Impact ◽  
Numerical Weather Prediction Models

<p>The low-level jet (LLJ) is an important phenomenon that can affect (and is affected by) the turbulence in the nocturnal urban boundary layer (UBL). We investigate the interaction of a regional LLJ with the UBL during a 2-day period over London. Observations from two Doppler Lidars and two numerical weather prediction models (Weather Research & Forecasting model and UKV Met Office Unified Model) are used to compared the LLJ characteristics (height, speed and fall-off) between a urban (London) and a rural (Chilbolton) site. We find that LLJs are elevated (70m) over London, due to the deeper UBL, an effect of the increased vertical mixing over the urban area and the difference in the topography between the two sites. Wind speed and fall-off are slightly reduced with respect to the rural LLJ. The effects of the urban area and the surrounding topography on the LLJ characteristics over London are isolated through idealized sensitivity experiments. We find that topography strongly affects the LLJ characteristics (height, falloff, and speed), but there is still a substantial urban influence.</p>

Surface Emissivity Impact on Temperature and Moisture Soundings from Hyperspectral Infrared Radiance Measurements

2011 ◽  
Vol 50 (6) ◽  
pp. 1225-1235 ◽  
Author(s):  
Zhigang Yao ◽  
Jun Li ◽  
Jinlong Li ◽  
Hong Zhang
Keyword(s):  
Land Surface ◽  
Prediction Models ◽  
Weather Prediction ◽  
Atmospheric Temperature ◽  
Retrieval Algorithm ◽  
Surface Emissivity ◽  
Angle Dependence ◽  
Infrared Radiance ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Impact

AbstractAn accurate land surface emissivity (LSE) is critical for the retrieval of atmospheric temperature and moisture profiles along with land surface temperature from hyperspectral infrared (IR) sounder radiances; it is also critical to assimilating IR radiances in numerical weather prediction models over land. To investigate the impact of different LSE datasets on Atmospheric Infrared Sounder (AIRS) sounding retrievals, experiments are conducted by using a one-dimensional variational (1DVAR) retrieval algorithm. Sounding retrievals using constant LSE, the LSE dataset from the Infrared Atmospheric Sounding Interferometer (IASI), and the baseline fit dataset from the Moderate Resolution Imaging Spectroradiometer (MODIS) are performed. AIRS observations over northern Africa on 1–7 January and 1–7 July 2007 are used in the experiments. From the limited regional comparisons presented here, it is revealed that the LSE from the IASI obtained the best agreement between the retrieval results and the ECMWF reanalysis, whereas the constant LSE gets the worst results when the emissivities are fixed in the retrieval process. The results also confirm that the simultaneous retrieval of atmospheric profile and surface parameters could reduce the dependence of soundings on the LSE choice and finally improve sounding accuracy when the emissivities are adjusted in the iterative retrieval. In addition, emissivity angle dependence is investigated with AIRS radiance measurements. The retrieved emissivity spectra from AIRS over the ocean reveal weak angle dependence, which is consistent with that from an ocean emissivity model. This result demonstrates the reliability of the 1DVAR simultaneous algorithm for emissivity retrieval from hyperspectral IR radiance measurements.

scholarly journals Impact Assessment of Daily Satellite-Derived Surface Albedo in a Limited-Area NWP Model

2012 ◽  
Vol 51 (10) ◽  
pp. 1835-1854 ◽  
Author(s):  
Jure Cedilnik ◽  
Dominique Carrer ◽  
Jean-François Mahfouf ◽  
Jean-Louis Roujean
Keyword(s):  
Land Surface ◽  
Short Range ◽  
Surface Albedo ◽  
Weather Prediction ◽  
A Priori ◽  
Limited Area ◽  
Model Biases ◽  
Nwp Model ◽  
The Impact ◽  
Range Forecasts

AbstractThis study examines the impact of daily satellite-derived albedos on short-range forecasts in a limited-area numerical weather prediction (NWP) model over Europe. Contrary to previous studies in which satellite products were used to derive monthly “climatologies,” a daily surface (snow free) albedo is analyzed by a Kalman filter. The filter combines optimally a satellite product derived from the Meteosat Second Generation geostationary satellite [and produced by the Land Surface Analyses–Satellite Application Facility of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT)], an albedo climatology, and a priori information given by “persistence.” The surface albedo analyzed for a given day is used as boundary conditions of the NWP model to run forecasts starting the following day. Results from short-range forecasts over a 1-yr period reveal the capacity of satellite information to reduce model biases and RMSE in screen-level temperature (during daytime and intermediate seasons). The impact on forecast scores is larger when considering the analyzed surface albedo rather than another climatologically based albedo product. From comparisons with measurements from three flux-tower stations over mostly homogeneous French forests, it is seen that the model biases in surface net radiation are significantly reduced. An impact on the whole planetary boundary layer, particularly in summer, results from the use of an observed surface albedo. An unexpected behavior produced in summer by the satellite-derived albedo on surface temperature is also explained. The forecast runs presented here, performed in dynamical adaptation mode, will be complemented later on by data assimilation experiments over typically monthly periods.

scholarly journals The Impact of Aeolus wind observations on the West African Monsoon

2021 ◽  
Author(s):  
Maurus Borne ◽  
Peter Knippertz ◽  
Martin Weissmann ◽  
Michael Rennie ◽  
Alexander Cress
Keyword(s):  
Weather Prediction ◽  
West African Monsoon ◽  
West African ◽  
Boreal Summer ◽  
Horizontal Line ◽  
The West ◽  
Great Opportunity ◽  
African Monsoon ◽  
The Difference ◽  
The Impact

<p>Tropical Africa is characterized by the world-wide largest degree of mesoscale convective organisation. During boreal summer, the wet phase of the West African Monsoon (WAM), the midlevel African easterly jet (AEJ) over the Sahel allows for the formation of synoptic-scale African easterly waves (AEWs) with a maximum intensity close to the West African coast. AEWs interact with convection and its mesoscale organization through modifications in humidity, temperature and vertical wind shear, and often serve as initial disturbances for tropical cyclogenesis. In addition, rainfall can be modulated by other types of tropical waves such as Kelvin or mixed Rossby gravity waves. Upper-tropospheric conditions are dominated by the Tropical Easterly Jet (TEJ), whose variability appears to be connected to convective activity. Overall, our quantitative understanding of the WAM system is still limited. The observational network over the region is sparse and rainfall forecasts with current Numerical Weather Prediction models are hardly better than climatology.</p><p>The Aeolus satellite launched in 2018 offers a great opportunity to further investigate the WAM with an unprecedented density of free-tropospheric wind data. Assimilating Aeolus wind observations in denial experiments using the current operational system of the European Centre for Medium-Range Weather Forecasts (ECMWF) shows that the main circulation features of the WAM are greatly impacted: the AEJ and the TEJ are systematically weaker and stronger respectively by~1m/s in the analysis fields including Aeolus data. As a consequence AEWs also show a weakening in the propagation amplitude. We are currently investigating the contributions of the HLOS (horizontal line-of-sight) Rayleigh and Mie wind observations to these observed differences. Mie observations (i.e., those related to backscatter from hydrometeors and aerosol particles) seems to contribute strongly to the difference in the AEJ, which lies within a convectively active region with a high aerosol load. On the other hand, the difference seen in the TEJ appears to originate mostly in the Rayleigh (i.e., clear air) observations. Surprisingly, the ascending and descending HLOS observations contribute differently to the data impact, possibly revealing a remaining bias or model problems with the diurnal cycle. Future work will include systematic comparisons between the operational systems of DWD and ECMWF to understand the influence of different data assimilation approaches as well as the impact on forecasts.</p>

Examining the Impact of SMAP Soil Moisture Retrievals on Short-Range Weather Prediction under Weakly and Strongly Coupled Data Assimilation with WRF-Noah

2019 ◽  
Vol 147 (12) ◽  
pp. 4345-4366 ◽  
Author(s):  
Liao-Fan Lin ◽  
Zhaoxia Pu
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Land Surface ◽  
Weather Prediction ◽  
Surface Model ◽  
Strongly Coupled ◽  
Soil Moisture Data ◽  
Analysis Scheme ◽  
Coupled Data Assimilation ◽  
The Impact

Abstract Remotely sensed soil moisture data are typically incorporated into numerical weather models under a framework of weakly coupled data assimilation (WCDA), with a land surface analysis scheme independent from the atmospheric analysis component. In contrast, strongly coupled data assimilation (SCDA) allows simultaneous correction of atmospheric and land surface states but has not been sufficiently explored with land surface soil moisture data assimilation. This study implemented a variational approach to assimilate the Soil Moisture Active Passive (SMAP) 9-km enhanced retrievals into the Noah land surface model coupled with the Weather Research and Forecasting (WRF) Model under a framework of both WCDA and SCDA. The goal of the study is to quantify the relative impact of assimilating SMAP data under different coupling frameworks on the atmospheric forecasts in the summer. The results of the numerical experiments during July 2016 show that SCDA can provide additional benefits on the forecasts of air temperature and humidity compared to WCDA. Over the U.S. Great Plains, assimilation of SMAP data under WCDA reduces a warm bias in temperature and a dry bias in humidity by 7.3% and 19.3%, respectively, while the SCDA case contributes an additional bias reduction of 2.2% (temperature) and 3.3% (humidity). While WCDA leads to a reduction of RMSE in temperature forecasts by 4.1%, SCDA results in additional reduction of RMSE by 0.8%. For the humidity, the reduction of RMSE is around 1% for both WCDA and SCDA.

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