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Earth observations were used to evaluate the representation of land surface temperature (LST) and vegetation coverage over Iberia in two state-of-the-art land surface models (LSMs) – the European Centre for Medium-Range Weather Forecasts (ECMWF) Carbon-Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land (CHTESSEL) and the Météo-France Interaction between Soil Biosphere and Atmosphere model (ISBA) within the SURface EXternalisée modeling platform (SURFEX-ISBA) for the 2004–2015 period. The results showed that the daily maximum LST simulated by CHTESSEL over Iberia was affected by a large cold bias during summer months when compared against the Satellite Application Facility on Land Surface Analysis (LSA-SAF), reaching magnitudes larger than 10 ∘C over wide portions of central and southwestern Iberia. This error was shown to be tightly linked to a misrepresentation of the vegetation cover. In contrast, SURFEX simulations did not display such a cold bias. We show that this was due to the better representation of vegetation cover in SURFEX, which uses an updated land cover dataset (ECOCLIMAP-II) and an interactive vegetation evolution, representing seasonality. The representation of vegetation over Iberia in CHTESSEL was improved by combining information from the European Space Agency Climate Change Initiative (ESA-CCI) land cover dataset with the Copernicus Global Land Service (CGLS) leaf area index (LAI) and fraction of vegetation coverage (FCOVER). The proposed improvement in vegetation also included a clumping approach that introduces seasonality to the vegetation cover. The results showed significant added value, removing the daily maximum LST summer cold bias completely, without reducing the accuracy of the simulated LST, regardless of season or time of the day. The striking performance differences between SURFEX and CHTESSEL were fundamental to guiding the developments in CHTESSEL highlighting the importance of using different models. This work has important implications: first, it takes advantage of LST, a key variable in surface–atmosphere energy and water exchanges, which is closely related to satellite top-of-atmosphere observations, to improve the model's representation of land surface processes. Second, CHTESSEL is the land surface model employed by ECMWF in the production of their weather forecasts and reanalysis; hence systematic errors in land surface variables and fluxes are then propagated into those products. Indeed, we showed that the summer daily maximum LST cold bias over Iberia in CHTESSEL is present in the widely used ECMWF fifth-generation reanalysis (ERA5). Finally, our results provided hints about the interaction between vegetation land–atmosphere exchanges, highlighting the relevance of the vegetation cover and respective seasonality in representing land surface temperature in both CHTESSEL and SURFEX. As a whole, this work demonstrated the added value of using multiple earth observation products for constraining and improving weather and climate simulations.
Miguel Nogueira; Clément Albergel; Souhail Boussetta; Frederico Johannsen; Isabel F. Trigo; Sofia L. Ermida; João P. A. Martins; Emanuel Dutra. Role of vegetation in representing land surface temperature in the CHTESSEL (CY45R1) and SURFEX-ISBA (v8.1) land surface models: a case study over Iberia. Geoscientific Model Development 2020, 13, 3975 -3993.
AMA StyleMiguel Nogueira, Clément Albergel, Souhail Boussetta, Frederico Johannsen, Isabel F. Trigo, Sofia L. Ermida, João P. A. Martins, Emanuel Dutra. Role of vegetation in representing land surface temperature in the CHTESSEL (CY45R1) and SURFEX-ISBA (v8.1) land surface models: a case study over Iberia. Geoscientific Model Development. 2020; 13 (9):3975-3993.
Chicago/Turabian StyleMiguel Nogueira; Clément Albergel; Souhail Boussetta; Frederico Johannsen; Isabel F. Trigo; Sofia L. Ermida; João P. A. Martins; Emanuel Dutra. 2020. "Role of vegetation in representing land surface temperature in the CHTESSEL (CY45R1) and SURFEX-ISBA (v8.1) land surface models: a case study over Iberia." Geoscientific Model Development 13, no. 9: 3975-3993.
Earth observations were used to evaluate the representation of Land Surface Temperature (LST) and vegetation coverage over Iberia in two state-of-the-art land surface models (LSMs) – the European Centre for Medium Range Weather Forecasting (ECMWF) Carbon-Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land (CHTESSEL) and the Météo-France Interaction between Soil Biosphere and Atmosphere model (ISBA) within the SURface EXternalisée modelling platform (SURFEX-ISBA) for the 2004–2015 period. The results show that the daily maximum LST simulated by CHTESSEL over Iberia is affected by a large cold bias during summer months when compared against the Satellite Application Facility on Land Surface Analysis (LSA-SAF), reaching magnitudes larger than 10 °C over wide portions of central and southwestern Iberia. This error is shown to be tightly linked to a misrepresentation of the vegetation cover. In contrast, SURFEX simulations did not display such a cold bias. We show that this was due to the better representation of vegetation cover in SURFEX, which uses an updated land cover dataset (ECOCLIMAP-II) and an interactive vegetation evolution, representing seasonality. The representation of vegetation over Iberia in CHTESSEL was improved by combining information from the European Space Agency Climate Change Initiative (ESA-CCI) land cover dataset with the Copernicus Global Land Service (CGLS) Leaf Area Index (LAI) and fraction of vegetation coverage (FCOVER). The proposed improvement in vegetation also includes a clumping approach that introduces seasonality to the vegetation cover. The results show significant added value, removing the daily maximum LST summer cold bias completely, without reducing the accuracy of the simulated LST, regardless of season or time of the day. The striking performance differences between SURFEX and CHTESSEL were fundamental to guide the developments in CHTESSEL highlighting the importance of using different models. This work has important implications: first, it takes advantage of LST, a key variable in surface-atmosphere energy and water exchanges, which is closely related to satellite top-of-atmosphere observations, to improve model’s representation of land surface processes. Second, CHTESSEL is the land surface model employed by ECMWF in the production of their weather forecasts and reanalysis, hence systematic errors in land surface variables and fluxes are then propagated into those products. Indeed, we show that the summer daily maximum LST cold bias over Iberia in CHTESSEL is present in the widely used ECMWF fifth generation reanalysis (ERA5). Finally, our results provide hints into the interaction between vegetation land-atmosphere exchanges, highlighting the relevance of the vegetation cover and respective seasonality in representing land surface temperature in both CHTESSEL and SURFEX. As a whole, this work demonstrates the added value in using multiple earth observation products for constraining and improving weather and climate simulations.
Miguel Nogueira; Clément Albergel; Souhail Boussetta; Frederico Johannsen; Isabel F Trigo; Sofia L Ermida; João P A Martins; Emanuel Dutra. Role of vegetation in representing land surface temperature in the CHTESSEL (CY45R1) and SURFEX-ISBA (v8.1) land surface models: a case study over Iberia. 2020, 2020, 1 -29.
AMA StyleMiguel Nogueira, Clément Albergel, Souhail Boussetta, Frederico Johannsen, Isabel F Trigo, Sofia L Ermida, João P A Martins, Emanuel Dutra. Role of vegetation in representing land surface temperature in the CHTESSEL (CY45R1) and SURFEX-ISBA (v8.1) land surface models: a case study over Iberia. . 2020; 2020 ():1-29.
Chicago/Turabian StyleMiguel Nogueira; Clément Albergel; Souhail Boussetta; Frederico Johannsen; Isabel F Trigo; Sofia L Ermida; João P A Martins; Emanuel Dutra. 2020. "Role of vegetation in representing land surface temperature in the CHTESSEL (CY45R1) and SURFEX-ISBA (v8.1) land surface models: a case study over Iberia." 2020, no. : 1-29.
Miguel Nogueira; Clément Albergel; Souhail Boussetta; Frederico Johannsen; Isabel F Trigo; Sofia L Ermida; João P A Martins; Emanuel Dutra. Supplementary material to "Role of vegetation in representing land surface temperature in the CHTESSEL (CY45R1) and SURFEX-ISBA (v8.1) land surface models: a case study over Iberia". 2020, 1 .
AMA StyleMiguel Nogueira, Clément Albergel, Souhail Boussetta, Frederico Johannsen, Isabel F Trigo, Sofia L Ermida, João P A Martins, Emanuel Dutra. Supplementary material to "Role of vegetation in representing land surface temperature in the CHTESSEL (CY45R1) and SURFEX-ISBA (v8.1) land surface models: a case study over Iberia". . 2020; ():1.
Chicago/Turabian StyleMiguel Nogueira; Clément Albergel; Souhail Boussetta; Frederico Johannsen; Isabel F Trigo; Sofia L Ermida; João P A Martins; Emanuel Dutra. 2020. "Supplementary material to "Role of vegetation in representing land surface temperature in the CHTESSEL (CY45R1) and SURFEX-ISBA (v8.1) land surface models: a case study over Iberia"." , no. : 1.
The EUMETSAT Land Surface Analysis Satellite Application Facility (LSA-SAF) now offers a wide range of satellite-derived products for land surface monitoring. The catalogue comprises variables quantifying different terms of the surface energy balance (land surface temperature – LST - and emissivity, downwelling radiative fluxes and turbulent fluxes), as well as several vegetation-related indicators, such as the Leaf Area Index, Fraction of Vegetation Cover, Evapotranspiration, Net Primary Production and Fire Radiative Power. The availability of these datasets, especially taking into account that the time series now span nearly two decades, already allows many interesting applications, overviewed in this presentation.
Comparisons of remote sensing data for land surfaces with corresponding model data have already been useful: the standard L2 (clear sky) LST has been used to diagnose a systematic cold bias of ERA5 skin temperature over the Iberian Peninsula. Offline simulations using H-TESSEL revealed that the bias could be alleviated using a more realistic representation of vegetation than what is currently used in ERA5. A recently developed product by LSA SAF allows LST retrievals for all-weather conditions, using a surface energy balance model to provide estimates under cloudy pixels. This product is compared to ERA5-Land skin temperature, showing that despite the increased level of detail of the latter (with respect to ERA5), it is still not representing the former correctly. ERA5 Land skin temperature shows large biases (of more than 10 K) and phase errors (with the satellite LST warming up prior to ERA-Land during the morning and cooling down earlier in the late afternoon). Comparisons of the different terms of the surface energy balance from ERA5-Land and LSA SAF are currently in progress to identify causes of the biases.
Another interesting application of LSA SAF products is the study of vegetation recovery over wild fire scars. Five wild fire events over Portugal were analyzed in terms of the long term anomalies introduced by the fire in 3 variables: LST, Albedo and Fraction of Vegetation Cover (all provided by LSA SAF). Results suggest that albedo returns to close-to-normal conditions in less than a year, while LST anomalies last much longer.
Finally, trends in the land-ocean thermal contrast were evaluated over Western Iberia and Northwest Africa (due to its importance in generating coastal mesoscale circulations). The study used long time series from 1) satellite – LST from CM-SAF and SST from GHRSST; 2) ERA5 global reanalysis and 3) UERRA regional reanalysis. The results strongly depend on the used dataset and sub-region, with UERRA showing a sharp decrease of the thermal contrast over Iberia, while ERA5 shows a positive trend.
These results emphasize the need to improve the representation of surface processes in numerical models, particularly over land surfaces. This presentation shows that datasets such as the ones provided by the LSA SAF are key to such improvements.
Joao Martins; Isabel Trigo; Mafalda Silva; Rita Cunha; Frederico Johannsen; Carlos Dacamara; Sofia Ermida; Emanuel Dutra; Célia Gouveia. Overview of applications of Remote Sensing Data Records and Reanalysis for the study of surface processes. 2020, 1 .
AMA StyleJoao Martins, Isabel Trigo, Mafalda Silva, Rita Cunha, Frederico Johannsen, Carlos Dacamara, Sofia Ermida, Emanuel Dutra, Célia Gouveia. Overview of applications of Remote Sensing Data Records and Reanalysis for the study of surface processes. . 2020; ():1.
Chicago/Turabian StyleJoao Martins; Isabel Trigo; Mafalda Silva; Rita Cunha; Frederico Johannsen; Carlos Dacamara; Sofia Ermida; Emanuel Dutra; Célia Gouveia. 2020. "Overview of applications of Remote Sensing Data Records and Reanalysis for the study of surface processes." , no. : 1.
A new all-weather land surface temperature (LST) product derived at the Satellite Application Facility on Land Surface Analysis (LSA-SAF) is presented. It is the first all-weather LST product based on visible and infrared observations combining clear-sky LST retrieved from the Spinning Enhanced Visible and Infrared Imager on Meteosat Second Generation (MSG/SEVIRI) infrared (IR) measurements with LST estimated with a land surface energy balance (EB) model to fill gaps caused by clouds. The EB model solves the surface energy balance mostly using products derived at LSA-SAF. The new product is compared with in situ observations made at 3 dedicated validation stations, and with a microwave (MW)-based LST product derived from Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) measurements. The validation against in-situ LST indicates an accuracy of the new product between -0.8 K and 1.1 K and a precision between 1.0 K and 1.4 K, generally showing a better performance than the MW product. The EB model shows some limitations concerning the representation of the LST diurnal cycle. Comparisons with MW LST generally show higher LST of the new product over desert areas, and lower LST over tropical regions. Several other imagers provide suitable measurements for implementing the proposed methodology, which offers the potential to obtain a global, nearly gap-free LST product.
João P. A. Martins; Isabel F. Trigo; Nicolas Ghilain; Carlos Jimenez; Frank-M. Göttsche; Sofia L. Ermida; Folke-S. Olesen; Françoise Gellens-Meulenberghs; Alirio Arboleda. An All-Weather Land Surface Temperature Product Based on MSG/SEVIRI Observations. Remote Sensing 2019, 11, 3044 .
AMA StyleJoão P. A. Martins, Isabel F. Trigo, Nicolas Ghilain, Carlos Jimenez, Frank-M. Göttsche, Sofia L. Ermida, Folke-S. Olesen, Françoise Gellens-Meulenberghs, Alirio Arboleda. An All-Weather Land Surface Temperature Product Based on MSG/SEVIRI Observations. Remote Sensing. 2019; 11 (24):3044.
Chicago/Turabian StyleJoão P. A. Martins; Isabel F. Trigo; Nicolas Ghilain; Carlos Jimenez; Frank-M. Göttsche; Sofia L. Ermida; Folke-S. Olesen; Françoise Gellens-Meulenberghs; Alirio Arboleda. 2019. "An All-Weather Land Surface Temperature Product Based on MSG/SEVIRI Observations." Remote Sensing 11, no. 24: 3044.
Land surface temperature (LST) is a key variable in surface-atmosphere energy and water exchanges. The main goals of this study are to (i) evaluate the LST of the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim and ERA5 reanalyses over Iberian Peninsula using the Satellite Application Facility on Land Surface Analysis (LSA-SAF) product and to (ii) understand the main drivers of the LST errors in the reanalysis. Simulations with the ECMWF land-surface model in offline mode (uncoupled) were carried out over the Iberian Peninsula and compared with the reanalysis data. Several sensitivity simulations were performed in a confined domain centered in Southern Portugal to investigate potential sources of the LST errors. The Copernicus Global Land Service (CGLS) fraction of green vegetation cover (FCover) and the European Space Agency’s Climate Change Initiative (ESA-CCI) Land Cover dataset were explored. We found a general underestimation of daytime LST and slightly overestimation at night-time. The results indicate that there is still room for improvement in the simulation of LST in ECMWF products. Still, ERA5 presents an overall higher quality product in relation to ERA-Interim. Our analysis suggested a relation between the large daytime cold bias and vegetation cover differences between (ERA5 and CGLS FCocver) with a correlation of −0.45. The replacement of the low and high vegetation cover by those of ESA-CCI provided an overall reduction of the large Tmax biases during summer. The increased vertical resolution of the soil at the surface, has a positive impact, but much smaller when compared with the vegetation changes. The sensitivity of the vegetation density parameter, that currently depends on the vegetation type, provided further proof for a needed revision of the vegetation in the model, as there is a reasonable correlation between this parameter and the Tmax mean errors when using the ESA-CCI vegetation cover (while the same correlation cannot be reproduced with the original model vegetation). Our results support the hypothesis that vegetation cover is one of the main drivers of the LST summertime cold bias in ERA5 over Iberian Peninsula.
Frederico Johannsen; Sofia Ermida; João P. A. Martins; Isabel F. Trigo; Miguel Nogueira; Emanuel Dutra. Cold Bias of ERA5 Summertime Daily Maximum Land Surface Temperature over Iberian Peninsula. Remote Sensing 2019, 11, 2570 .
AMA StyleFrederico Johannsen, Sofia Ermida, João P. A. Martins, Isabel F. Trigo, Miguel Nogueira, Emanuel Dutra. Cold Bias of ERA5 Summertime Daily Maximum Land Surface Temperature over Iberian Peninsula. Remote Sensing. 2019; 11 (21):2570.
Chicago/Turabian StyleFrederico Johannsen; Sofia Ermida; João P. A. Martins; Isabel F. Trigo; Miguel Nogueira; Emanuel Dutra. 2019. "Cold Bias of ERA5 Summertime Daily Maximum Land Surface Temperature over Iberian Peninsula." Remote Sensing 11, no. 21: 2570.
Land surface temperature (LST) is a key variable in surface-atmosphere energy and water exchanges. The main goals of this study are to (i) evaluate the LST of the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim and ERA5 reanalyses over Iberian Peninsula using the Satellite Application Facility on Land Surface Analysis (LSA-SAF) product and to (ii) understand the main drivers of the LST errors in the reanalysis. Simulations with the ECMWF land-surface model in offline mode (uncoupled) were carried out over the Iberian Peninsula and compared with the reanalysis data. Several sensitivity simulations were performed in a confined domain centered in Southern Portugal to investigate potential sources of the LST errors. The Copernicus Global Land Service (CGLS) fraction of green vegetation cover (FCover) and the European Space Agency’s Climate Change Initiative (ESA-CCI) Land Cover dataset were explored. We found a general underestimation of daytime LST and slightly overestimation at night-time. The results indicate that there is still room for improvement in the simulation of LST in ECMWF products. Still, ERA5 presents an overall higher quality product in relation to ERA-Interim. Our analysis suggested a relation between the large daytime cold bias and vegetation cover differences between (ERA5 and CGLS FCocver) with a correlation of -0.45. The replacement of the low and high vegetation cover by those of ESA-CCI provided an overall reduction of the large Tmax biases during summer. The increased vertical resolution of the soil at the surface, has a positive impact, but much smaller when compared with the vegetation changes. The sensitivity of the vegetation density parameter, that currently depends on the vegetation type, provided further proof for a needed revision of the vegetation in the model, as there is a reasonable correlation between this parameter and the Tmax mean errors when using the ESA-CCI vegetation cover (while the same correlation cannot be reproduced with the original model vegetation). Our results support the hypothesis that vegetation cover is one of the main drivers of the LST summertime cold bias in ERA5 over Iberian Peninsula.
Frederico Johannsen; Sofia Ermida; João Martins; Isabel F. Trigo; Miguel Nogueira; Emanuel Dutra. Cold Bias of ERA5 Summertime Daily Maximum Land Surface Temperature Over Iberian Peninsula. 2019, 1 .
AMA StyleFrederico Johannsen, Sofia Ermida, João Martins, Isabel F. Trigo, Miguel Nogueira, Emanuel Dutra. Cold Bias of ERA5 Summertime Daily Maximum Land Surface Temperature Over Iberian Peninsula. . 2019; ():1.
Chicago/Turabian StyleFrederico Johannsen; Sofia Ermida; João Martins; Isabel F. Trigo; Miguel Nogueira; Emanuel Dutra. 2019. "Cold Bias of ERA5 Summertime Daily Maximum Land Surface Temperature Over Iberian Peninsula." , no. : 1.
The global-scale patterns and covariances of subtropical marine boundary layer (MBL) cloud fraction and spatial variability with atmospheric thermodynamic and dynamic fields remain poorly understood. We describe an approach that leverages coincident NASA A-train and the Modern Era Retrospective-Analysis for Research and Applications (MERRA) data to quantify the relationships in the subtropical MBL derived at the native pixel and grid resolution. A new method for observing four subtropical oceanic regions that capture transitions from stratocumulus to trade cumulus is demonstrated, where stratocumulus and cumulus regimes are determined from infrared-based thermodynamic phase. Visible radiances are normally distributed within stratocumulus and are increasingly skewed away from the coast, where trade cumulus dominates. Increases in MBL depth, wind speed, and effective radius (re), and reductions in 700–1000 hPa moist static energy differences and 700 and 850 hPa vertical velocity correspond with increases in visible radiance skewness. We posit that a more robust representation of the cloudy MBL is obtained using visible radiance rather than retrievals of optical thickness that are limited to a smaller subset of cumulus. The method using the combined A-train and MERRA data set has demonstrated that an increase in re within shallow cumulus is strongly related to higher MBL wind speeds that further correspond to increased precipitation occurrence according to CloudSat, previously demonstrated with surface observations. Hence, the combined data sets have the potential of adding global context to process-level understanding of the MBL.
Brian H. Kahn; Georgios Matheou; Qing Yue; Thomas Fauchez; Eric J. Fetzer; Matthew Lebsock; João Martins; Mathias M. Schreier; Kentaroh Suzuki; João Teixeira. An A-train and MERRA view of cloud, thermodynamic, and dynamic variability within the subtropical marine boundary layer. Atmospheric Chemistry and Physics 2017, 17, 9451 -9468.
AMA StyleBrian H. Kahn, Georgios Matheou, Qing Yue, Thomas Fauchez, Eric J. Fetzer, Matthew Lebsock, João Martins, Mathias M. Schreier, Kentaroh Suzuki, João Teixeira. An A-train and MERRA view of cloud, thermodynamic, and dynamic variability within the subtropical marine boundary layer. Atmospheric Chemistry and Physics. 2017; 17 (15):9451-9468.
Chicago/Turabian StyleBrian H. Kahn; Georgios Matheou; Qing Yue; Thomas Fauchez; Eric J. Fetzer; Matthew Lebsock; João Martins; Mathias M. Schreier; Kentaroh Suzuki; João Teixeira. 2017. "An A-train and MERRA view of cloud, thermodynamic, and dynamic variability within the subtropical marine boundary layer." Atmospheric Chemistry and Physics 17, no. 15: 9451-9468.
The global-scale patterns and covariances of subtropical marine boundary layer (MBL) cloud fraction and spatial organization with atmospheric thermodynamic and dynamic fields remain poorly understood. We describe a novel approach that leverages coincident NASA A-train and the Modern Era Retrospective-Analysis for Research and Applications (MERRA) data to quantify the relationships in the subtropical MBL derived at the native pixel and grid resolution. Four subtropical oceanic regions that capture transitions from closed-cell stratocumulus to open-cell trade cumulus are investigated. We define stratocumulus and cumulus regimes based exclusively from infrared-based thermodynamic phase. Visible reflectances are normally distributed within stratocumulus and are increasingly skewed away from the coast where disorganized cumulus dominates. Increases in MBL depth, wind speed and effective radius (re), and reductions in 700–1000 hPa moist static energy differences and 700 and 850 hPa vertical velocity, correspond with increases in reflectance skewness. We posit that a more robust representation of the cloudy MBL is obtained using visible reflectance rather than retrievals of optical thickness that are limited to a smaller subset of cumulus. An increase in re within shallow cumulus is strongly related to higher MBL wind speeds that further correspond to increased precipitation occurrence according to CloudSat. Our results are consistent with surface-based observations and suggest that the combination of A-train and MERRA data sets have potential to add global context to our process understanding of the subtropical cumulus-dominated MBL.
Brian H. Kahn; Georgios Matheou; Qing Yue; Thomas Fauchez; Eric J. Fetzer; Matthew Lebsock; João Martins; Mathias M. Schreier; Kentaroh Suzuki; João Teixeira. A satellite and reanalysis view of cloud organization, thermodynamic, and dynamic variability within the subtropical marine boundary layer. 2017, 2017, 1 -34.
AMA StyleBrian H. Kahn, Georgios Matheou, Qing Yue, Thomas Fauchez, Eric J. Fetzer, Matthew Lebsock, João Martins, Mathias M. Schreier, Kentaroh Suzuki, João Teixeira. A satellite and reanalysis view of cloud organization, thermodynamic, and dynamic variability within the subtropical marine boundary layer. . 2017; 2017 ():1-34.
Chicago/Turabian StyleBrian H. Kahn; Georgios Matheou; Qing Yue; Thomas Fauchez; Eric J. Fetzer; Matthew Lebsock; João Martins; Mathias M. Schreier; Kentaroh Suzuki; João Teixeira. 2017. "A satellite and reanalysis view of cloud organization, thermodynamic, and dynamic variability within the subtropical marine boundary layer." 2017, no. : 1-34.
Algorithms for Land Surface Temperature (LST) retrieval from infrared measurements are usually sensitive to the amount of water vapor present in the atmosphere. The Satellite Application Facilities on Climate Monitoring and Land Surface Analysis (CM SAF and LSA SAF) are currently compiling a 25 year LST Climate data record (CDR), which uses water vapor information from ERA-Int reanalysis. However, its relatively coarse spatial resolution may lead to systematic errors in the humidity profiles with implications in LST, particularly over mountainous areas. The present study compares LST estimated with three different retrieval algorithms: a radiative transfer-based physical mono-window (PMW), a statistical mono-window (SMW), and a generalized split-windows (GSW). The algorithms were tested over the Alpine region using ERA-Int reanalysis data and relied on the finer spatial scale Consortium for Small-Scale Modelling (COSMO) model data as a reference. Two methods were developed to correct ERA-Int water vapor misestimation: (1) an exponential parametrization of total precipitable water (TPW) appropriate for SMW/GSW; and (2) a level reduction method to be used in PMW. When ERA-Int TPW was used, the algorithm missed the right TPW class in 87% of the cases. When the exponential parametrization was used, the missing class rate decreased to 9%, and when the level reduction method was applied, the LST corrections went up to 1.7 K over the study region. Overall, the correction for pixel orography in TPW leads to corrections in LST estimations, which are relevant to ensure that long-term LST records meet climate requirements, particularly over mountainous regions.
Virgílio A. Bento; Carlos C. DaCamara; Isabel F. Trigo; João P. A. Martins; Anke Duguay-Tetzlaff. Improving Land Surface Temperature Retrievals over Mountainous Regions. Remote Sensing 2017, 9, 38 .
AMA StyleVirgílio A. Bento, Carlos C. DaCamara, Isabel F. Trigo, João P. A. Martins, Anke Duguay-Tetzlaff. Improving Land Surface Temperature Retrievals over Mountainous Regions. Remote Sensing. 2017; 9 (1):38.
Chicago/Turabian StyleVirgílio A. Bento; Carlos C. DaCamara; Isabel F. Trigo; João P. A. Martins; Anke Duguay-Tetzlaff. 2017. "Improving Land Surface Temperature Retrievals over Mountainous Regions." Remote Sensing 9, no. 1: 38.
Land surface temperature (LST) is routinely retrieved from remote sensing instruments using semi-empirical relationships between top of atmosphere (TOA) radiances and LST, using ancillary data such as total column water vapor or emissivity. These algorithms are calibrated using a set of forward radiative transfer simulations that return the TOA radiances given the LST and the thermodynamic profiles. The simulations are done in order to cover a wide range of surface and atmospheric conditions and viewing geometries. This study analyzes calibration strategies while considering some of the most critical factors that need to be taken into account when building a calibration dataset, covering the full dynamic range of relevant variables. A sensitivity analysis of split-windows and single channel algorithms revealed that selecting a set of atmospheric profiles that spans the full range of surface temperatures and total column water vapor combinations that are physically possible seems beneficial for the quality of the regression model. However, the calibration is extremely sensitive to the low-level structure of the atmosphere, indicating that the presence of atmospheric boundary layer features such as temperature inversions or strong vertical gradients of thermodynamic properties may affect LST retrievals in a non-trivial way. This article describes the criteria established in the EUMETSAT Land Surface Analysis—Satellite Application Facility to calibrate its LST algorithms, applied both for current and forthcoming sensors.
João P. A. Martins; Isabel F. Trigo; Virgílio A. Bento; Carlos Da Camara. A Physically Constrained Calibration Database for Land Surface Temperature Using Infrared Retrieval Algorithms. Remote Sensing 2016, 8, 808 .
AMA StyleJoão P. A. Martins, Isabel F. Trigo, Virgílio A. Bento, Carlos Da Camara. A Physically Constrained Calibration Database for Land Surface Temperature Using Infrared Retrieval Algorithms. Remote Sensing. 2016; 8 (10):808.
Chicago/Turabian StyleJoão P. A. Martins; Isabel F. Trigo; Virgílio A. Bento; Carlos Da Camara. 2016. "A Physically Constrained Calibration Database for Land Surface Temperature Using Infrared Retrieval Algorithms." Remote Sensing 8, no. 10: 808.
Land Surface Temperature (LST) is routinely retrieved from remote sensing instruments using semi-empirical relationships between top of atmosphere (TOA) radiances and LST, using ancillary data such as total column water vapor or emissivity. These algorithms are calibrated using a set of forward radiative transfer simulations that return the TOA radiances given the LST and the thermodynamic profiles. The simulations are done in order to cover a wide range of surface and atmospheric conditions and viewing geometries. This work analyses calibration strategies, considering some of the most critical factors that need to be taken into account when building a calibration dataset, covering the full dynamic range of relevant variables. A sensitivity analysis of split-windows and single channel algorithms revealed that selecting a set of atmospheric profiles that spans the full range of surface temperatures and total column water vapor combinations that are physically possible seems beneficial for the quality of the regression model. However, the calibration is extremely sensitive to the low-level structure of the atmosphere indicating that the presence of atmospheric boundary layer features such as temperature inversions or strong vertical gradients of thermodynamic properties may affect LST retrievals in a non-trivial way. This article describes the criteria established in the EUMETSAT Land Surface Analysis – Satellite Application Facility to calibrate its LST algorithms applied both for current and forthcoming sensors.
João P. A. Martins; Isabel F. Trigo; Virgílio A. Bento; Carlos Da Camara. A Physically-Constrained Calibration Database for Land Surface Temperature Using Infrared Retrieval Algorithms. 2016, 1 .
AMA StyleJoão P. A. Martins, Isabel F. Trigo, Virgílio A. Bento, Carlos Da Camara. A Physically-Constrained Calibration Database for Land Surface Temperature Using Infrared Retrieval Algorithms. . 2016; ():1.
Chicago/Turabian StyleJoão P. A. Martins; Isabel F. Trigo; Virgílio A. Bento; Carlos Da Camara. 2016. "A Physically-Constrained Calibration Database for Land Surface Temperature Using Infrared Retrieval Algorithms." , no. : 1.
The European Organization for the Exploitation of Meteorological Satellites’ (EUMETSAT) Meteosat satellites provide the unique opportunity to compile a 30+ year land surface temperature (LST) climate data record. Since the Meteosat instrument on-board Meteosat 2–7 is equipped with a single thermal channel, single-channel LST retrieval algorithms are used to ensure consistency across Meteosat satellites. The present study compares the performance of two single-channel LST retrieval algorithms: (1) A physical radiative transfer-based mono-window (PMW); and (2) a statistical mono-window model (SMW). The performance of the single-channel algorithms is assessed using a database of synthetic radiances for a wide range of atmospheric profiles and surface variables. The two single-channel algorithms are evaluated against the commonly-used generalized split-window (GSW) model. The three algorithms are verified against more than 60,000 LST ground observations with dry to very moist atmospheres (total column water vapor (TCWV) 1–56 mm). Except for very moist atmospheres (TCWV > 45 mm), results show that Meteosat single-channel retrievals match those of the GSW algorithm by 0.1–0.5 K. This study also outlines that it is possible to put realistic uncertainties on Meteosat single-channel LSTs, except for very moist atmospheres: simulated theoretical uncertainties are within 0.3–1.0 K of the in situ root mean square differences for TCWV < 45 mm.
Anke Duguay-Tetzlaff; Virgílio A. Bento; Frank M. Göttsche; Reto Stöckli; João P. A. Martins; Isabel Trigo; Folke Olesen; Jedrzej Bojanowski; Carlos Da Camara; Heike Kunz. Meteosat Land Surface Temperature Climate Data Record: Achievable Accuracy and Potential Uncertainties. Remote Sensing 2015, 7, 13139 -13156.
AMA StyleAnke Duguay-Tetzlaff, Virgílio A. Bento, Frank M. Göttsche, Reto Stöckli, João P. A. Martins, Isabel Trigo, Folke Olesen, Jedrzej Bojanowski, Carlos Da Camara, Heike Kunz. Meteosat Land Surface Temperature Climate Data Record: Achievable Accuracy and Potential Uncertainties. Remote Sensing. 2015; 7 (10):13139-13156.
Chicago/Turabian StyleAnke Duguay-Tetzlaff; Virgílio A. Bento; Frank M. Göttsche; Reto Stöckli; João P. A. Martins; Isabel Trigo; Folke Olesen; Jedrzej Bojanowski; Carlos Da Camara; Heike Kunz. 2015. "Meteosat Land Surface Temperature Climate Data Record: Achievable Accuracy and Potential Uncertainties." Remote Sensing 7, no. 10: 13139-13156.
The summer time cloud diurnal cycle over western Iberia is analysed here using a satellite climate data record of fractional cloud cover based on 9 years of Meteosat Second Generation observations which is distributed by the EUMETSAT's Climate Monitoring Satellite Applications Facility. These observations were complemented with a corresponding mean cloud diurnal cycle using SYNOP reports on six locations over the studied domain. It is shown that the main coastal mountain range separates regions that are characterized by two very different cloud regimes: stratocumulus‐topped boundary layer convection dominates the region towards the coast and continental cumulus convection dominates the region to the east of these mountains. To explain the observed variability, a long‐term regional climate model [Weather Research and Forecasting model (WRF)] simulation over Iberia was used. A comparison of the observations against model output for the common period between observations and simulation shows that although the model generally underestimates cloudiness, it is able to represent the diurnal cycle in a realistic manner. It is shown that the observed cloud diurnal evolution is linked to the thermal circulations generated by the land‐sea contrast and orography. The extent to which the cloud deck penetrates inland is closely related to the coastal orography: although smaller hills tend to enhance cloudiness, larger mountains block the progression of the marine boundary layer further inland, as it behaves as a density current. Larger mountains also produce katabatic flow and a rather strong subsidence aloft during the night. The warming due to this subsidence helps the blocking of the cloud deck as it is partially responsible for evaporating clouds, as shown by a potential temperature budget analysis.
João P. A. Martins; Rita M. Cardoso; Pedro Soares; Isabel Trigo; Margarida Belo-Pereira; Nuno Moreira; Ricardo Tomé. The summer diurnal cycle of coastal cloudiness over west Iberia using Meteosat/SEVIRI and a WRF regional climate model simulation. International Journal of Climatology 2015, 36, 1755 -1772.
AMA StyleJoão P. A. Martins, Rita M. Cardoso, Pedro Soares, Isabel Trigo, Margarida Belo-Pereira, Nuno Moreira, Ricardo Tomé. The summer diurnal cycle of coastal cloudiness over west Iberia using Meteosat/SEVIRI and a WRF regional climate model simulation. International Journal of Climatology. 2015; 36 (4):1755-1772.
Chicago/Turabian StyleJoão P. A. Martins; Rita M. Cardoso; Pedro Soares; Isabel Trigo; Margarida Belo-Pereira; Nuno Moreira; Ricardo Tomé. 2015. "The summer diurnal cycle of coastal cloudiness over west Iberia using Meteosat/SEVIRI and a WRF regional climate model simulation." International Journal of Climatology 36, no. 4: 1755-1772.
A model evaluation approach is proposed in which weather and climate prediction models are analyzed along a Pacific Ocean cross section, from the stratocumulus regions off the coast of California, across the shallow convection dominated trade winds, to the deep convection regions of the ITCZ—the Global Energy and Water Cycle Experiment Cloud System Study/Working Group on Numerical Experimentation (GCSS/WGNE) Pacific Cross-Section Intercomparison (GPCI). The main goal of GPCI is to evaluate and help understand and improve the representation of tropical and subtropical cloud processes in weather and climate prediction models. In this paper, a detailed analysis of cloud regime transitions along the cross section from the subtropics to the tropics for the season June–July–August of 1998 is presented. This GPCI study confirms many of the typical weather and climate prediction model problems in the representation of clouds: underestimation of clouds in the stratocumulus regime by most models with the corresponding consequences in terms of shortwave radiation biases; overestimation of clouds by the 40-yr ECMWF Re-Analysis (ERA-40) in the deep tropics (in particular) with the corresponding impact in the outgoing longwave radiation; large spread between the different models in terms of cloud cover, liquid water path and shortwave radiation; significant differences between the models in terms of vertical cross sections of cloud properties (in particular), vertical velocity, and relative humidity. An alternative analysis of cloud cover mean statistics is proposed where sharp gradients in cloud cover along the GPCI transect are taken into account. This analysis shows that the negative cloud bias of some models and ERA-40 in the stratocumulus regions [as compared to the first International Satellite Cloud Climatology Project (ISCCP)] is associated not only with lower values of cloud cover in these regimes, but also with a stratocumulus-to-cumulus transition that occurs too early along the trade wind Lagrangian trajectory. Histograms of cloud cover along the cross section differ significantly between models. Some models exhibit a quasi-bimodal structure with cloud cover being either very large (close to 100%) or very small, while other models show a more continuous transition. The ISCCP observations suggest that reality is in-between these two extreme examples. These different patterns reflect the diverse nature of the cloud, boundary layer, and convection parameterizations in the participating weather and climate prediction models.
Jose Teixeira; Silvana S S Cardoso; M. Bonazzola; Jason N S Cole; Anthony D DelGenio; Charlotte A DeMott; Charmaine Franklin; Cecile Hannay; Christian Jakob; Y. Jiao; Johannes Karlsson; H. Kitagawa; M. Köhler; Akira Kuwano-Yoshida; C. LeDrian; J. Li; A P Lock; Mark J Miller; Pablo A Marquet; Joao Martins; Carlos R Mechoso; Erik Van Meijgaard; I. Meinke; Pedro Miranda; Dmitrii Mironov; R A J Neggers; H. L. Pan; David Randall; Philip J Rasch; Burkhardt Rockel; William B Rossow; Barbara A Ritter; A. P. Siebesma; Pedro Soares; Francis Joseph Turk; Paul A Vaillancourt; A. Von Engeln; M. Zhao. Tropical and Subtropical Cloud Transitions in Weather and Climate Prediction Models: The GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI). Journal of Climate 2011, 24, 5223 -5256.
AMA StyleJose Teixeira, Silvana S S Cardoso, M. Bonazzola, Jason N S Cole, Anthony D DelGenio, Charlotte A DeMott, Charmaine Franklin, Cecile Hannay, Christian Jakob, Y. Jiao, Johannes Karlsson, H. Kitagawa, M. Köhler, Akira Kuwano-Yoshida, C. LeDrian, J. Li, A P Lock, Mark J Miller, Pablo A Marquet, Joao Martins, Carlos R Mechoso, Erik Van Meijgaard, I. Meinke, Pedro Miranda, Dmitrii Mironov, R A J Neggers, H. L. Pan, David Randall, Philip J Rasch, Burkhardt Rockel, William B Rossow, Barbara A Ritter, A. P. Siebesma, Pedro Soares, Francis Joseph Turk, Paul A Vaillancourt, A. Von Engeln, M. Zhao. Tropical and Subtropical Cloud Transitions in Weather and Climate Prediction Models: The GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI). Journal of Climate. 2011; 24 (20):5223-5256.
Chicago/Turabian StyleJose Teixeira; Silvana S S Cardoso; M. Bonazzola; Jason N S Cole; Anthony D DelGenio; Charlotte A DeMott; Charmaine Franklin; Cecile Hannay; Christian Jakob; Y. Jiao; Johannes Karlsson; H. Kitagawa; M. Köhler; Akira Kuwano-Yoshida; C. LeDrian; J. Li; A P Lock; Mark J Miller; Pablo A Marquet; Joao Martins; Carlos R Mechoso; Erik Van Meijgaard; I. Meinke; Pedro Miranda; Dmitrii Mironov; R A J Neggers; H. L. Pan; David Randall; Philip J Rasch; Burkhardt Rockel; William B Rossow; Barbara A Ritter; A. P. Siebesma; Pedro Soares; Francis Joseph Turk; Paul A Vaillancourt; A. Von Engeln; M. Zhao. 2011. "Tropical and Subtropical Cloud Transitions in Weather and Climate Prediction Models: The GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI)." Journal of Climate 24, no. 20: 5223-5256.
[1] The new generation of remote sensors on board NASA's A‐Train constellation offers the possibility of observing the atmospheric boundary layer in different regimes, with or without clouds. In this study we use data from the Atmospheric InfraRed Sounder (AIRS) and of the Rain In Cumulus over the Ocean (RICO) campaign, to verify the accuracy and precision of the AIRS Version 5 Level 2 support product. This AIRS product has an improved vertical sampling that is necessary for the estimation of boundary layer properties. Good agreement is found between AIRS and RICO data, in a regime of oceanic shallow cumulus that is known to be difficult to analyze with other remote sensing data, and also shows a low sensitivity to cloud or land fraction. This suggests that AIRS data may be used for global boundary layer studies to support parameterization development in regions of difficult in‐situ observation.
João P. A. Martins; João Teixeira; Pedro M. M. Soares; Pedro M. A. Miranda; Brian H. Kahn; Van T. Dang; Frederick W. Irion; Eric J. Fetzer; Evan Fishbein. Infrared sounding of the trade-wind boundary layer: AIRS and the RICO experiment. Geophysical Research Letters 2010, 37, 1 .
AMA StyleJoão P. A. Martins, João Teixeira, Pedro M. M. Soares, Pedro M. A. Miranda, Brian H. Kahn, Van T. Dang, Frederick W. Irion, Eric J. Fetzer, Evan Fishbein. Infrared sounding of the trade-wind boundary layer: AIRS and the RICO experiment. Geophysical Research Letters. 2010; 37 (24):1.
Chicago/Turabian StyleJoão P. A. Martins; João Teixeira; Pedro M. M. Soares; Pedro M. A. Miranda; Brian H. Kahn; Van T. Dang; Frederick W. Irion; Eric J. Fetzer; Evan Fishbein. 2010. "Infrared sounding of the trade-wind boundary layer: AIRS and the RICO experiment." Geophysical Research Letters 37, no. 24: 1.
Hugo Terças; J P A Martins; José Tito Mendonça. Rossby waves in rapidly rotating Bose–Einstein condensates. New Journal of Physics 2010, 12, 1 .
AMA StyleHugo Terças, J P A Martins, José Tito Mendonça. Rossby waves in rapidly rotating Bose–Einstein condensates. New Journal of Physics. 2010; 12 (9):1.
Chicago/Turabian StyleHugo Terças; J P A Martins; José Tito Mendonça. 2010. "Rossby waves in rapidly rotating Bose–Einstein condensates." New Journal of Physics 12, no. 9: 1.
The impact of a new approach to the evaluation of surface gravity wave drag (GWD) is assessed. This approach uses linear theory, but incorporates the effects of wind profile shear and curvature, by means of a second‐order WKB approximation. While the theory predicts the possibility of either drag enhancement or reduction, depending on the wind profile, results obtained with the ERA‐40 reanalysis data clearly indicate the predominance of local drag enhancement. However, the global impact of shear on the atmospheric axial GWD torque comes mostly from regions with predominantly easterly flow, contributing to a slight reduction of the bias found in different studies of the global angular momentum budget. The relative correction due to shear on linear GWD is found not to depend too strongly on the levels chosen for the computation of the low‐level wind derivatives. Copyright © 2009 Royal Meteorological Society
P. M. A. Miranda; J. P. A. Martins; M. A. C. Teixeira. Assessing wind profile effects on the global atmospheric torque. Quarterly Journal of the Royal Meteorological Society 2009, 135, 807 -814.
AMA StyleP. M. A. Miranda, J. P. A. Martins, M. A. C. Teixeira. Assessing wind profile effects on the global atmospheric torque. Quarterly Journal of the Royal Meteorological Society. 2009; 135 (640):807-814.
Chicago/Turabian StyleP. M. A. Miranda; J. P. A. Martins; M. A. C. Teixeira. 2009. "Assessing wind profile effects on the global atmospheric torque." Quarterly Journal of the Royal Meteorological Society 135, no. 640: 807-814.