Downscaling landsat land surface temperature over the urban area of Florence

A new downscaling algorithm for land surface temperature (LST) images retrieved from Landsat Thematic Mapper (TM) was developed over the city of Florence and the results assessed against a high-resolution aerial image. The Landsat TM thermal band has a spatial resolution of 120 m, resampled at 30 m by the US Geological Survey (USGS) agency, whilst the airborne ground spatial resolution was 1 m. Substantial differences between Landsat USGS and airborne thermal data were observed on a 30 m grid: therefore a new statistical downscaling method at 30 m was developed. The overall root mean square error with respect to aircraft data improved from 3.3 °C (USGS) to 3.0 °C with the new method, that also showed better results with respect to other regressive downscaling techniques frequently used in literature. Such improvements can be ascribed to the selection of independent variables capable of representing the heterogeneous urban landscape

WRF wind field assessment under multiple forcings using spatialized aircraft data

AbstractThe performances of limited area weather models are affected by the choice of core solvers, domain resolutions, and initial and boundary conditions. To understand the extent of such differences on simulated wind fields, weather research and forecast (WRF) simulations initialized by different forcings were extensively compared with an aircraft‐derived high‐resolution data set. The two used forcings were the European Centre for Medium‐Range Weather Forecasts (ECMWF) ERA‐Interim reanalysis and the National Centers for Environmental Predictions (NCEP) Climate Forecast System Reanalysis (CFSR). The model domain covered a large portion of central western Italy (including part of the Tyrrhenian coast) encompassing the aircraft track and allowed the characterization of their performance across the simulation domain rather than a small set of point‐based observations. The WRF results show good agreement with the aircraft data across the whole flight track with both forcings (root mean square errors (RMSEs) < 2.3 m·s−1 and an average r2 = 0.7). Orography and coasts show an effect on simulated wind fields. The presence of a strong orography (which is smoothed by the model internal terrain elevation model) is associated with increased errors. Distance from the coast is also associated with a variation in RMSE (even if in a non‐straightforward manner) because of potential breeze effects. No forcing data set clearly outperforms the other, while the ECMWF has higher correlation co‐efficients when considering wind direction

Carbon Dioxide Emissions of the City Center of Firenze, Italy: Measurement, Evaluation, and Source Partitioning

AbstractAn eddy covariance station was installed in the city center of Firenze, Italy, to measure carbon fluxes at half-hourly intervals over a mostly homogeneous urban area. Carbon dioxide (CO2) emission observations made over an initial period of 3.5 months were compared with indirect estimates of CO2 emissions based on inventory data sources of vehicle circulation and natural gas consumption for domestic heating and cooking. Such a comparison provided proper evaluation of the measurements. Using seasonal dynamics of observed fluxes, the overall CO2 source of the city center was partitioned into its major components (i.e., road traffic and domestic heating). Results were directly compared with CO2 source estimates based on inventory sources

Increased CO₂ loss from vegetated drained lake tundra ecosystems due to flooding

Tundra ecosystems are especially sensitive to climate change, which is particularly rapid in high northern latitudes resulting in significant alterations in temperature and soil moisture. Numerous studies have demonstrated that soil drying increases the respiration loss from wet Arctic tundra. And, warming and drying of tundra soils are assumed to increase CO2 emissions from the Arctic. However, in this water table manipulation experiment (i.e., flooding experiment), we show that flooding of wet tundra can also lead to increased CO2 loss. Standing water increased heat conduction into the soil, leading to higher soil temperature, deeper thaw and, surprisingly, to higher CO2 loss in the most anaerobic of the experimental areas. The study site is located in a drained lake basin, and the soils are characterized by wetter conditions than upland tundra. In experimentally flooded areas, high wind speeds (greater than ~4 m s−1) increased CO2 emission rates, sometimes overwhelming the photosynthetic uptake, even during daytime. This suggests that CO2 efflux from C rich soils and surface waters can be limited by surface exchange processes. The comparison of the CO2 and CH4 emission in an anaerobic soil incubation experiment showed that in this ecosystem, CO2 production is an order of magnitude higher than CH4 production. Future increases in surface water ponding, linked to surface subsidence and thermokarst erosion, and concomitant increases in soil warming, can increase net C efflux from these arctic ecosystems

Temperature Response of Respiration Across the Heterogeneous Landscape of the Alaskan Arctic Tundra

AbstractPredictions of the response of ecosystem respiration to warming in the Arctic are not well constrained, partly due to the considerable spatial heterogeneity of these permafrost‐dominated areas. Accurate calculations of in situ temperature sensitivities of respiration (Q10) are vital for the prediction of future Arctic emissions. To understand the impact of spatial heterogeneity on respiration rates and Q10, we compared respiration measured from automated chambers across the main local polygonized landscape forms (high and low centers, polygon rims, polygon troughs) to estimates from the flux‐partitioned net ecosystem exchange collected in an adjacent eddy covariance tower. Microtopographic type appears to be the most important variable explaining the variability in respiration rates, and low‐center polygons and polygon troughs show the greatest cumulative respiration rates, possibly linked to their deeper thaw depth and higher plant biomass. Regardless of the differences in absolute respiration rates, Q10 is surprisingly similar across all microtopographic features, possibly indicating a similar temperature limitation to decomposition across the landscape. Q10 was higher during the colder early summer and lower during the warmer peak growing season, consistent with an elevated temperature sensitivity under colder conditions. The respiration measured by the chambers and the estimates from the daytime flux‐partitioned eddy covariance data were within uncertainties during early and peak seasons but overestimated respiration later in the growing season. Overall, this study suggests that it is possible to simplify estimates of the temperature sensitivity of respiration across heterogeneous landscapes but that seasonal changes in Q10 should be incorporated into model simulations

Retrieving soil moisture in rainfed and irrigated fields using Sentinel-2 observations and a modified OPTRAM approach

Abstract Surface soil water content plays an important role in driving the exchange of latent and sensible heat between the atmosphere and land surface through transpiration and evaporation processes, regulating key physiological processes affecting plants growth. Given the high impact of water scarcity on yields, and of irrigated agriculture on the overall withdrawal rate of freshwater, it is important to define models that help to improve water resources management for agricultural purposes, and to optimize rainfed crop yield. Recent advances in satellite-based remote sensing have led to valuable solutions to estimate soil water content based on microwave or optical/thermal-infrared data. This study aims at improving soil water content estimation at high spatial and temporal resolution, by means of the Optical Trapezoid Model (OPTRAM) driven by Copernicus Sentinel-2 data. Two different model variations were considered, based on linear and nonlinear parameters constraints, and validated against in situ soil water content measurements made with time domain reflectometry (TDR) on irrigated maize in central Italy and on rainfed maize and pasture in northern Italy. For the first site the non-linear model shows a better correlation between measured and estimated soil water content values (r = 0.80) compared to the linear model (r = 0.73). In both cases the modeled soil moisture tends to overestimate the measured values at medium to high water content level, while both models underestimate soil moisture at low water content level. Estimated versus measured normalized surface soil water for rainfed pasture plots from nonlinear OPTRAM parametrized based on irrigated maize parameterization (SIM1), and site-specific parametrization for rainfed pasture (SIM2), indicate that both models (SIM1 and SIM2) are comparable for rotational grazing pasture (RMSEsim1 = 0.0581 vs. RMSEsim2 = 0.0485 cm3 cm-3) and the continuous grazing pasture (RMSEsim1 = 0.0485 vs. RMSEsim2 = 0.0602 cm3 cm-3), while for the rainfed maize plots SIM1 shows lower RMSE (average for all plots RMSE = 0.0542 cm3 cm-3) compared to the site-specific calibration model (SIM2 – average for all plots RMSE = 0.0645 cm3 cm-3). Finally, OPTRAM estimations are close to in situ measurement values while Surface Soil Moisture at 1 km (SSM1 km) tends to underestimate the measurements during maize crop growing season. Soil moisture retrieval from high-resolution Sentinel-2 optical images allows water stress conditions to be effectively mapped, supporting decision making in irrigation scheduling and other crop management

Development of a Novel Framework for the Assessment and Improvement of Climate Adaptation and Mitigation Actions in Europe

The greenhouse gases (GHG) emissions in the European Union (EU) are mainly caused by human activity from five sectors—power, industry, transport, buildings, and agriculture. To tackle all these challenges, the EU actions and policies have been encouraging initiatives focusing on a holistic approach but these initiatives are not enough coordinated and connected to reach the much needed impact. To strengthen the important role of regions in climate actions, and stimulate wide stakeholders’ engagement including citizens, a conceptual framework for enabling rapid and far-reaching climate actions through multi-sectoral regional adaptation pathways is hereby developed. The target audience for this framework is composed by regional policy makers, developers and fellow scientists. The scale of the framework emphasizes the regional function as an important meeting point and delivery arena for European and national climate strategies and objectives both at urban and rural level. The framework is based on transformative and no-regret measures, prioritizing the Key Community Systems (KCS) that most urgently need to be protected from climate impacts and risks.publishedVersio

Greenhouse gas emissions from urban area of Naples

Urban areas are among the main causes of greenhouse gases emissions on the planet, despite covering relatively small areas of the land. Recently, a number of projects aim at monitoring the dynamics of city emissions using micro meteorological measurements by applying the technique of eddy correlation for measuring the fluxes of carbon dioxide, water, methane and energy. In this perspective, a super-site for the measurement of atmospheric pollutants from urban sources has been established in Naples (Campania, Southern Italy), where the complex layout of the coast and surrounding mountains favours the development of combined sea breeze upslope winds and the evolution of return flows with several layers of pollutants and subsidence. At the super-site, an eddy covariance tower has been installed on the rooftop of the Meteorological Observatory of Largo San Marcellino, situated in the historical city centre: a fast response ultrasonic anemometer (Gill WindMaster) has been mounted on a 10-m mast, alongside three insulated inlet lines through which the air is sampled for gaseous pollutants and particulate matter. The height of the terrace is on average 35 m above the irregular street level, resulting in an overall measuring height of 45 m. Mixing ratios of CO2, CH4 and H2O are measured by an infrared spectrometer (10 Hz, Los Gatos Research). The results shown that the mean urban levels of CO2 are between 420-520 ppm; the mean levels of CH4 span between 1.85-2.48 ppm. These fluxes are representative of varying footprint source areas, covering the historical centre of Naples, the harbour, and some main traffic arteries of the city. The analysis of these measurements on long-term will allow to establish relationships between the fluxes of greenhouse gases and the other pollutant species measured