The EarthCARE satellite: the next step forward in global measurements of clouds, aerosols, precipitation, and radiation

The collective representation within global models of aerosol, cloud, precipitation, and their radiative properties remains unsatisfactory. They constitute the largest source of uncertainty in predictions of climatic change and hamper the ability of numerical weather prediction models to forecast high-impact weather events. The joint European Space Agency (ESA)–Japan Aerospace Exploration Agency (JAXA) Earth Clouds, Aerosol and Radiation Explorer (EarthCARE) satellite mission, scheduled for launch in 2018, will help to resolve these weaknesses by providing global profiles of cloud, aerosol, precipitation, and associated radiative properties inferred from a combination of measurements made by its collocated active and passive sensors. EarthCARE will improve our understanding of cloud and aerosol processes by extending the invaluable dataset acquired by the A-Train satellites CloudSat, Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and Aqua. Specifically, EarthCARE’s cloud profiling radar, with 7 dB more sensitivity than CloudSat, will detect more thin clouds and its Doppler capability will provide novel information on convection, precipitating ice particle, and raindrop fall speeds. EarthCARE’s 355-nm high-spectral-resolution lidar will measure directly and accurately cloud and aerosol extinction and optical depth. Combining this with backscatter and polarization information should lead to an unprecedented ability to identify aerosol type. The multispectral imager will provide a context for, and the ability to construct, the cloud and aerosol distribution in 3D domains around the narrow 2D retrieved cross section. The consistency of the retrievals will be assessed to within a target of ±10 W m–2 on the (10 km)2 scale by comparing the multiview broadband radiometer observations to the top-of-atmosphere fluxes estimated by 3D radiative transfer models acting on retrieved 3D domains.

Exploiting satellite-based rainfall for weather index insurance: the challenges of spatial and temporal aggregation

Lack of access to insurance exacerbates the impact of climate variability on smallholder famers in Africa. Unlike traditional insurance, which compensates proven agricultural losses, weather index insurance (WII) pays out in the event that a weather index is breached. In principle, WII could be provided to farmers throughout Africa. There are two data-related hurdles to this. First, most farmers do not live close enough to a rain gauge with sufficiently long record of observations. Second, mismatches between weather indices and yield may expose farmers to uncompensated losses, and insurers to unfair payouts – a phenomenon known as basis risk. In essence, basis risk results from complexities in the progression from meteorological drought (rainfall deficit) to agricultural drought (low soil moisture). In this study, we use a land-surface model to describe the transition from meteorological to agricultural drought. We demonstrate that spatial and temporal aggregation of rainfall results in a clearer link with soil moisture, and hence a reduction in basis risk. We then use an advanced statistical method to show how optimal aggregation of satellite-based rainfall estimates can reduce basis risk, enabling remotely sensed data to be utilized robustly for WII.

On the development of summer thunderstorms in the city of Sao Paulo: Mean meteorological characteristics and pollution effect

This study investigates how the summer thunderstorms developed over the city of Sao Paulo and if the pollution might affect its development or characteristics during the austral summer (December-January-February-March, DJFM months). A total of 605 days from December 1999 to March 2004 was separated as 241 thunderstorms days (TDs) and 364 non-thunderstorm days (NTDs). The analyses are performed by using hourly measurements of air temperature (T), web-bulb temperature (Tw), surface atmospheric pressure (P), wind velocity and direction, rainfall and thunder and lightning observations collected at the Meteorological Station of the University of Sao Paulo in conjunction with aerosol measurements obtained by AERONET (Aerosol Robotic Network), and the NCEP-DOE (National Centers for Environmental Prediction Department of Energy) reanalysis and radiosondes. The wind diurnal cycle shows that for TDs the morning flow is from the northwest rotating to the southeast after 16: 00 local time (LT) and it remains from the east until the night. For the NTDs, the wind is well characterized by the sea-breeze circulation that in the morning has the wind blowing from the northeast and in the afternoon from the southeast. The TDs show that the air temperature diurnal cycle presents higher amplitude and the maximum temperature of the day is 3.2 degrees C higher than in NTDs. Another important factor found is the difference between moisture that is higher during TDs. In terms of precipitation, the TDs represent 40% of total of days analyzed and those days are responsible for more than 60% of the total rain accumulation during the summer, for instance 50% of the TDs had more than 15.5mm day(-1) while the NTDs had 4 mm day(-1). Moreover, the rainfall distribution shows that TDs have higher rainfall rate intensities and an afternoon precipitation maximum; while in the NTDs there isn`t a defined precipitation diurnal cycle. The wind and temperature fields from NCEP reanalysis concur with the local weather station and radiosonde observations. The NCEP composites show that TDs are controlled by synoptic circulation characterized by a pre-frontal situation, with a baroclinic zone situated at southern part of Sao Paulo. In terms of pollution, this study employed the AERONET data to obtain the main aerosol characteristics in the atmospheric column for both TDs and NTDs. The particle size distribution and particle volume size distribution have similar concentrations for both TDs and NTDs and present a similar fine and coarse mode mean radius. In respect to the atmospheric loading, the aerosol optical depth (AOD) at different frequencies presented closed mean values for both TDs and NTDs that were statistically significant at 95% level. The spectral dependency of those values in conjunction with the Angstrom parameter reveal the higher concentration of the fine mode particles that are more likely to be hygroscopic and from urban areas. In summary, no significant aerosol effect could be found on the development of summer thunderstorms, suggesting the strong synoptic control by the baroclinic forcing for deep convective development. (C) 2010 Published by Elsevier B. V.

A dense GNSS meteorological network for observing deep convection in the Amazon

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Aumento della risoluzione spaziale per il sondaggio di temperatura e umidità da satellite geostazionario mediante radiometria ad onde millimetriche e submillimetriche

The purpose of this study is to develop and evaluate techniques that improve the spatial resolution of the channels already selected in the preliminary studies for Geostationary Observatory for Microwave Atmospheric Soundings (GOMAS). Reference high resolution multifrequency brightness temperatures scenarios have been derived by applying radiative transfer calculation to the spatially and microphysically detailed output of meteorological events simulated by the University of Wisconsin - Non-hydrostatic Model System (UW-NMS). Three approaches, Wiener filter, Super-Resolution and Image Fusion have been applied to some representative GOMAS frequency channels to enhance the resolution of antenna temperatures. The Wiener filter improved resolution of the largely oversampled images by a factor 1.5- 2.0 without introducing any penalty in the radiometric accuracy. Super-resolution, suitable for not largely oversampled images, improved resolution by a factor ~1.5 but introducing an increased radiometric noise by a factor 1.4-2.5. The image fusion allows finally to further increase the spatial frequency of the images obtained by the Wiener filter increasing the total resolution up to a factor 5.0 with an increased radiometric noise closely linked to the radiometric frequency and to the examined case study.

A satellite-based snow cover climatology (1985–2011) for the European Alps derived from AVHRR data

Seasonal snow cover is of great environmental and socio-economic importance for the European Alps. Therefore a high priority has been assigned to quantifying its temporal and spatial variability. Complementary to land-based monitoring networks, optical satellite observations can be used to derive spatially comprehensive information on snow cover extent. For understanding long-term changes in alpine snow cover extent, the data acquired by the Advanced Very High Resolution Radiometer (AVHRR) sensors mounted onboard the National Oceanic and Atmospheric Association (NOAA) and Meteorological Operational satellite (MetOp) platforms offer a unique source of information. In this paper, we present the first space-borne 1 km snow extent climatology for the Alpine region derived from AVHRR data over the period 1985–2011. The objective of this study is twofold: first, to generate a new set of cloud-free satellite snow products using a specific cloud gap-filling technique and second, to examine the spatiotemporal distribution of snow cover in the European Alps over the last 27 yr from the satellite perspective. For this purpose, snow parameters such as snow onset day, snow cover duration (SCD), melt-out date and the snow cover area percentage (SCA) were employed to analyze spatiotemporal variability of snow cover over the course of three decades. On the regional scale, significant trends were found toward a shorter SCD at lower elevations in the south-east and south-west. However, our results do not show any significant trends in the monthly mean SCA over the last 27 yr. This is in agreement with other research findings and may indicate a deceleration of the decreasing snow trend in the Alpine region. Furthermore, such data may provide spatially and temporally homogeneous snow information for comprehensive use in related research fields (i.e., hydrologic and economic applications) or can serve as a reference for climate models.

Introduction to the Maïdo Lidar Calibration Campaign dedicated to the validation of upper air meteorological parameters

The first operations at the new High-altitude Maïdo Observatory at La Réunion began in 2013. The Maïdo Lidar Calibration Campaign (MALICCA) was organized there in April 2013 and has focused on the validation of the thermodynamic parameters (temperature, water vapor, and wind) measured with many instruments including the new very large lidar for water vapor and temperature profiles. The aim of this publication consists of providing an overview of the different instruments deployed during this campaign and their status, some of the targeted scientific questions and associated instrumental issues. Some specific detailed studies for some individual techniques were addressed elsewhere. This study shows that temperature profiles were obtained from the ground to the mesopause (80 km) thanks to the lidar and regular meteorological balloon-borne sondes with an overlap range showing good agreement. Water vapor is also monitored from the ground to the mesopause by using the Raman lidar and microwave techniques. Both techniques need to be pushed to their limit to reduce the missing range in the lower stratosphere. Total columns obtained from global positioning system or spectrometers are valuable for checking the calibration and ensuring vertical continuity. The lidar can also provide the vertical cloud structure that is a valuable complementary piece of information when investigating the water vapor cycle. Finally, wind vertical profiles, which were obtained from sondes, are now also retrieved at Maïdo from the newly implemented microwave technique and the lidar. Stable calibrations as well as a small-scale dynamical structure are required to monitor the thermodynamic state of the middle atmosphere, ensure validation of satellite sensors, study the transport of water vapor in the vicinity of the tropical tropopause and study their link with cirrus clouds and cyclones and the impact of small-scale dynamics (gravity waves) and their link with the mean state of the mesosphere.

Fluxes and meteorological observations on Spitsbergen

Arctic permafrost may be adversely affected by climate change in a number of ways, so that establishing a world-wide monitoring program seems imperative. This thesis evaluates possibilities for permafrost monitoring at the example of a permafrost site on Svalbard, Norway. An energy balance model for permafrost temperatures is developed that evaluates the different components of the surface energy budget in analogy to climate models. The surface energy budget, consisting of radiation components, sensible and latent heat fluxes as well as the ground heat flux, is measured over the course of one year, which has not been accomplished for arctic land areas so far. A considerable small-scale heterogeneity of the summer surface temperature is observed in long-term measurements with a thermal imaging system, which can be reproduced in the energy balance model. The model can also simulate the impact of different snow depths on the soil temperature, that has been documented in field measurements. Furthermore, time series of terrestrial surface temperature measurements are compared to satellite-borne measurements, for which a significant cold-bias is observed during winter. Finally, different possibilities for a world-wide monitoring scheme are assessed. Energy budget models can incorporate different satellite data sets as training data sets for parameter estimation, so that they may constitute an alternative to purely satellite-based schemes.

Satellite-based daily lake areas in the Yangtze Basin, China, 2000-2011

The Yangtze River Basin downstream of China's Three Gorges Dam (TGD) (thereafter referred to as "downstream" basin) hosts the largest cluster of freshwater lakes in East Asia. These lakes are crucial water stocks to local biophysical environments and socioeconomic development. Existing studies document that individual lakes in this region have recently experienced dramatic changes under the context of enduring meteorological drought, continuous population growth, and extensive water regulation since TGD's initial impoundment (i.e., June, 2003). However, spatial and temporal patterns of lake dynamics across the complete downstream Yangtze basin remain poorly characterized. Using daily MODIS imagery and an advanced thematic mapping scheme, this study presents a comprehensive monitoring of area dynamics in the downstream lake system at a 10-day temporal resolution during 2000-2011. The studied lakes constitute ~76% (~11,400 km**2) of the total downstream lake area, including the entire +70 major lakes larger than 20 km**2. The results reveal a decadal net decline in lake inundation area across the downstream Yangtze Basin, with a cumulative decrease of 849 km**2 or 7.4% from 2000 to 2011. Despite an excessive precipitation anomaly in the year 2010, the decreasing trend was tested significant in all seasons. The most substantial decrease in the post-TGD period appears in fall (1.1%/yr), which intriguingly coincides with the TGD water storage season. Regional lake dynamics exhibit contrasting spatial patterns, manifested as evident decrease and increase of aggregated lake areas respectively within and beyond the Yangtze Plain. This contrast suggests a marked vulnerability of lakes in the Yangtze Plain, to not only local meteorological variability but also intensified human water regulations from both the upstream Yangtze main stem (e.g., the TGD) and tributaries (e.g., lakes/reservoirs beyond the Yangtze Plain). The produced lake mapping result and derived lake area dynamics across the downstream Yangtze Basin provides a crucial monitoring basis for continuous investigations of changing mechanisms in the Yangtze lake system.

Significant achievements in satellite meterology 1958-1964.

Mode of access: Internet.

NOAA satellite programs briefing.

"August 1983."

Key to meteorological records documentation

Mode of access: Internet.

Neural network-based wind vector retrieval from satellite scatterometer data

Obtaining wind vectors over the ocean is important for weather forecasting and ocean modelling. Several satellite systems used operationally by meteorological agencies utilise scatterometers to infer wind vectors over the oceans. In this paper we present the results of using novel neural network based techniques to estimate wind vectors from such data. The problem is partitioned into estimating wind speed and wind direction. Wind speed is modelled using a multi-layer perceptron (MLP) and a sum of squares error function. Wind direction is a periodic variable and a multi-valued function for a given set of inputs; a conventional MLP fails at this task, and so we model the full periodic probability density of direction conditioned on the satellite derived inputs using a Mixture Density Network (MDN) with periodic kernel functions. A committee of the resulting MDNs is shown to improve the results.

Neural network-based wind vector retrieval from satellite scatterometer data

Obtaining wind vectors over the ocean is important for weather forecasting and ocean modelling. Several satellite systems used operationally by meteorological agencies utilise scatterometers to infer wind vectors over the oceans. In this paper we present the results of using novel neural network based techniques to estimate wind vectors from such data. The problem is partitioned into estimating wind speed and wind direction. Wind speed is modelled using a multi-layer perceptron (MLP) and a sum of squares error function. Wind direction is a periodic variable and a multi-valued function for a given set of inputs; a conventional MLP fails at this task, and so we model the full periodic probability density of direction conditioned on the satellite derived inputs using a Mixture Density Network (MDN) with periodic kernel functions. A committee of the resulting MDNs is shown to improve the results.

The use of Meteosat satellite data for spatial rainfall estimations and hydrological simulations

Satellite information, in combination with conventional point source measurements, can be a valuable source of information. This thesis is devoted to the spatial estimation of areal rainfall over a region using both the measurements from a dense and sparse network of rain-gauges and images from the meteorological satellites. A primary concern is to study the effects of such satellite assisted rainfall estimates on the performance of rainfall-runoff models. Low-cost image processing systems and peripherals are used to process and manipulate the data. Both secondary as well as primary satellite images were used for analysis. The secondary data was obtained from the in-house satellite receiver and the primary data was obtained from an outside source. Ground truth data was obtained from the local Water Authority. A number of algorithms are presented that combine the satellite and conventional data sources to produce areal rainfall estimates and the results are compared with some of the more traditional methodologies. The results indicate that the satellite cloud information is valuable in the assessment of the spatial distribution of areal rainfall, for both half-hourly as well as daily estimates of rainfall. It is also demonstrated how the performance of the simple multiple regression rainfall-runoff model is improved when satellite cloud information is used as a separate input in addition to rainfall estimates from conventional means. The use of low-cost equipment, from image processing systems to satellite imagery, makes it possible for developing countries to introduce such systems in areas where the benefits are greatest.