A new satellite-based global climatology of dust aerosol optical depth

By mass, dust is the largest contributor to global aerosol burden, yet long-term observational records of dust, particularly over the ocean, are limited. Here, two nearly global observational datasets of dust aerosol optical depth τd are created primarily on the basis of optical measurements of the aerosol column from 1) the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite spanning from 2001 to 2018 and 2) the Advanced Very High Resolution Radiometer (AVHRR) from 1981 to 2018. The quality of the new data is assessed by comparison with existing dust datasets that are spatially more limited. Between 2001 and 2018, τd decreased over Asia and increased significantly over the Sahara, Middle East, and parts of eastern Europe, with the largest increase found over the Aral Sea where emissive playa surfaces have been exposed. These daily, observational, and nearly global records of dust will allow for improvement in understanding the role of dust in climate variability

Satellite and in situ observations for advancing global Earth surface modelling: a review

In this paper, we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort

An automated and improved methodology to retrieve long-time series of evapotranspiration based on remote sensing and reanalysis data

The large-scale quantification of accurate evapotranspiration (ET) time series has substantially been developed in recent decades using automated approaches based on remote sensing data. However, there are still several model-related uncertainties that require precise assessment. In this study, the Surface Energy Balance Algorithm for Land (SEBAL) and meteorological data from the Global Land Data Assimilation System (GLDAS) were used to estimate long-term daily actual ET based on three endmember selection procedures: two land cover-based models, one with (WF) and the other without (WOF) morphological functions, and the Allen method (with the default percentiles) for 2270 Landsat images. Models were evaluated for 23 flux tower sites with four main vegetation cover types as well as different climate types. Results showed that endmember selection with morphological functions (WF_ET) generally performed better than the other endmember approaches. Climate-based classification assessment provided the clearest discrimination between the performance of the different endmember selection approaches for the humid category. For humid zones, the land cover-based methods, especially WF, appropriately outperformed Allen. However, the performance of the three approaches was similar for sub-humid, semi-arid and arid climates together; the Allen approach was therefore recommended to avoid the need for dependency on land cover maps. Tower-by-tower validation also showed that the WF approach performed best at 12 flux tower sites, the WOF approach best at 5 and the Allen approach best at 6, suggesting that the use of land cover maps alone does not explain the differences between the performance of the land cover-based models and the Allen approach. Additionally, the satisfactory error metrics results when comparing the EC estimations with EC measurements, with root mean square error (RMSE) ≈ 0.91 and 1.59 mm·day−1, coefficient of determination (R2) ≈ 0.71 and 0.41, and bias percentage (PBias) ≈ 2% and 60% for crop and non-crop flux tower sites, respectively, supports the use of GLDAS meteorological forcing datasets with the different automated ET estimation approaches. Overall, given that the thorough evaluation of different endmember selection approaches at large scale confirmed the validity of the WF approach for different climate and land cover types, this study can be considered an important contribution to the global retrieval of long time series of ETinfo:eu-repo/semantics/publishedVersio

Air–Sea Interaction in the Central Mediterranean Sea: Assessment of Reanalysis and Satellite Observations

Air–sea heat fluxes are essential climate variables, required for understanding air–sea interactions, local, regional and global climate, the hydrological cycle and atmospheric and oceanic circulation. In situ measurements of fluxes over the ocean are sparse and model reanalysis and satellite data can provide estimates at different scales. The accuracy of such estimates is therefore essential to obtain a reliable description of the occurring phenomena and changes. In this work, air–sea radiative fluxes derived from the SEVIRI sensor onboard the MSG satellite and from ERA5 reanalysis have been compared to direct high quality measurements performed over a complete annual cycle at the ENEA oceanographic observatory, near the island of Lampedusa in the Central Mediterranean Sea. Our analysis reveals that satellite derived products overestimate in situ direct observations of the downwelling short-wave (bias of 6.1 W/m2) and longwave (bias of 6.6 W/m2) irradiances. ERA5 reanalysis data show a negligible positive bias (+1.0 W/m2) for the shortwave irradiance and a large negative bias (−17 W/m2) for the longwave irradiance with respect to in situ observations. ERA5 meteorological variables, which are needed to calculate the air–sea heat flux using bulk formulae, have been compared with in situ measurements made at the oceanographic observatory. The two meteorological datasets show a very good agreement, with some underestimate of the wind speed by ERA5 for high wind conditions. We investigated the impact of different determinations of heat fluxes on the near surface sea temperature (1 m depth), as determined by calculations with a one-dimensional numerical model, the General Ocean Turbulence Model (GOTM). The sensitivity of the model to the different forcing was measured in terms of differences with respect to in situ temperature measurements made during the period under investigation. All simulations reproduced the true seasonal cycle and all high frequency variabilities. The best results on the overall seasonal cycle were obtained when using meteorological variables in the bulk formulae formulations used by the model itself. The derived overall annual net heat flux values were between +1.6 and 40.4 W/m2, depending on the used dataset. The large variability obtained with different datasets suggests that current determinations of the heat flux components and, in particular, of the longwave irradiance, need to be improved. The ENEA oceanographic observatory provides a complete, long-term, high resolution time series of high quality in situ observations. In the future, more similar sites worldwide will be needed for model and satellite validations and to improve the determination of the air–sea exchange and the understanding of related processes

RADIATIVE FLUXES AND ALBEDO FEEDBACK IN POLAR REGIONS

The Arctic is experiencing an unprecedented increase in surface temperature and decrease in sea ice extent. Discussion as to the causes that contribute to the Arctic warming is still ongoing. The ice-albedo feedback has been proposed as a possible mechanism for polar amplification of such warming. It states that more open water leads to more solar heat absorption, which results in more ice melting and more open water. In order to study this relationship there is a need for accurate information on the solar heat input into the Arctic Oceans. I have developed and improved inference schemes for shortwave radiative fluxes that respond to the needs of Polar Regions utilizing most recent information on atmospheric and surface states. A Moderate Resolution Imaging Spectroradiometer (MODIS) approach has been optimized for Polar Regions and implemented at 1° for 2002-2010 and at 5-km for 2007. A methodology was developed to derive solar fluxes from the Advanced Very High Resolution Radiometer (AVHRR) and implemented at 0.5° for 1983-2006. Evaluation against ground measurements over land and ocean at high latitudes shows that the MODIS shortwave flux estimates are in best agreement with ground observations as compared to other available satellite and model products, with a bias of -3.6 Wm-2 and standard deviation of 23 Wm-2 at a daily time scale. The AVHRR estimates agree with ground observations with a bias of -4.7 Wm-2 and a standard deviation of 41 Wm-2 at a daily time scale. The ice-albedo feedback was evaluated by computing the solar heating into the Arctic Ocean using the improved satellite flux estimates. A growth at a rate of 2 %/year in the trend of solar heating for 2003-09 was found at a 75 % confidence level; the trend for 1984-2002 was only 0.2 %/year at a 99 % confidence level. The ice retreat is correlated to the solar energy into the ocean at 0.7 at a 75 % confidence level. An increase in the open water fraction resulted in a maximum 300 % positive anomaly in solar heating in 2007 located where the maximum sea ice retreat is

Research priorities in land use and land-cover change for the Earth System and Integrated Assessment Modelling

This special issue has highlighted recent and innovative methods and results that integrate observations and modelling analyses of regional to global aspect of biophysical and biogeochemical interactions of land-cover change with the climate system. Both the Earth System and the Integrated Assessment modeling communities recognize the importance of an accurate representation of land use and land-cover change to understand and quantify the interactions and feedbacks with the climate and socio-economic systems, respectively. To date, cooperation between these communities has been limited. Based on common interests, this work discusses research priorities in representing land use and land-cover change for improved collaboration across modelling, observing and measurement communities. Major research topics in land use and land-cover change are those that help us better understand (1) the interaction of land use and land cover with the climate system (e.g. carbon cycle feedbacks), (2) the provision of goods and ecosystem services by terrestrial (natural and anthropogenic) land-cover types (e.g. food production), (3) land use and management decisions and (4) opportunities and limitations for managing climate change (for both mitigation and adaptation strategies