Observations of supercooling and frazil ice formation in the Laptev Sea coastal polynya

This paper examines a hydrographic response to the wind‐driven coastal polynya activity over the southeastern Laptev Sea shelf for April–May 2008, using a combination of Environmental Satellite (Envisat) advanced synthetic aperture radar (ASAR) and TerraSAR‐X satellite imagery, aerial photography, meteorological data, and SBE‐37 salinity‐temperature‐depth and acoustic Doppler current profiler land‐fast ice edgemoored instruments. When ASAR observed the strongest end‐of‐April polynya event with frazil ice formation, the moored instruments showed maximal acoustical scattering within the surface mixed layer, and the seawater temperatures were either at or 0.02°C below freezing. We also find evidence of the persistent horizontal temperature and salinity gradients across the fast ice edge to have the signature of geostrophic flow adjustment as predicted by polynya models.

Earth's ion upflow associated with polar cap patches: global and in-situ observations

We report simultaneous global monitoring of a patch of ionization and in situ observation of ion upflow at the center of the polar cap region during a geomagnetic storm. Our observations indicate strong fluxes of upwelling O+ ions originating from frictional heating produced by rapid antisunward flow of the plasma patch. The statistical results from the crossings of the central polar cap region by Defense Meteorological Satellite Program F16–F18 from 2010 to 2013 confirm that the field-aligned flow can turn upward when rapid antisunward flows appear, with consequent significant frictional heating of the ions, which overcomes the gravity effect. We suggest that such rapidly moving patches can provide an important source of upwelling ions in a region where downward flows are usually expected. These observations give new insight into the processes of ionosphere-magnetosphere coupling.

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.

Seasonal drought stress in the Amazon: Reconciling models and observations

The Amazon Basin is crucial to global circulatory and carbon patterns due to the large areal extent and large flux magnitude. Biogeophysical models have had difficulty reproducing the annual cycle of net ecosystem exchange (NEE) of carbon in some regions of the Amazon, generally simulating uptake during the wet season and efflux during seasonal drought. In reality, the opposite occurs. Observational and modeling studies have identified several mechanisms that explain the observed annual cycle, including: (1) deep soil columns that can store large water amount, (2) the ability of deep roots to access moisture at depth when near-surface soil dries during annual drought, (3) movement of water in the soil via hydraulic redistribution, allowing for more efficient uptake of water during the wet season, and moistening of near-surface soil during the annual drought, and (4) photosynthetic response to elevated light levels as cloudiness decreases during the dry season. We incorporate these mechanisms into the third version of the Simple Biosphere model (SiB3) both singly and collectively, and confront the results with observations. For the forest to maintain function through seasonal drought, there must be sufficient water storage in the soil to sustain transpiration through the dry season in addition to the ability of the roots to access the stored water. We find that individually, none of these mechanisms by themselves produces a simulation of the annual cycle of NEE that matches the observed. When these mechanisms are combined into the model, NEE follows the general trend of the observations, showing efflux during the wet season and uptake during seasonal drought.

Satellite Rainfall Estimates Over South America - Possible Applicability to the Water Management of Large Watersheds1

This work analyzes high-resolution precipitation data from satellite-derived rainfall estimates over South America, especially over the Amazon Basin. The goal is to examine whether satellite-derived precipitation estimates can be used in hydrology and in the management of larger watersheds of South America. High spatial-temporal resolution precipitation estimates obtained with the CMORPH method serve this purpose while providing an additional hydrometeorological perspective on the convective regime over South America and its predictability. CMORPH rainfall estimates at 8-km spatial resolution for 2003 and 2004 were compared with available rain gauge measurements at daily, monthly, and yearly accumulation time scales. The results show the correlation between satellite-derived and gauge-measured precipitation increases with accumulation period from daily to monthly, especially during the rainy season. Time-longitude diagrams of CMORPH hourly rainfall show the genesis, strength, longevity, and phase speed of convective systems. Hourly rainfall analyses indicate that convection over the Amazon region is often more organized than previously thought, thus inferring that basin scale predictions of rainfall for hydrological and water management purposes have the potential to become more skillful. Flow estimates based on CMORPH and the rain gauge network are compared to long-term observed average flow. The results suggest this satellite-based rainfall estimation technique has considerable utility. Other statistics for monthly accumulations also suggest CMORPH can be an important source of rainfall information at smaller spatial scales where in situ observations are lacking.

Combining Satellite And Gauge Precipitation Data With Co-Kriging Method For Jakarta Region

Jakarta is vulnerable to flooding mainly caused by prolonged and heavy rainfall and thus a robust hydrological modeling is called for. A good quality of spatial precipitation data is therefore desired so that a good hydrological model could be achieved. Two types of rainfall sources are available: satellite and gauge station observations. At-site rainfall is considered to be a reliable and accurate source of rainfall. However, the limited number of stations makes the spatial interpolation not very much appealing. On the other hand, the gridded rainfall nowadays has high spatial resolution and improved accuracy, but still, relatively less accurate than its counterpart. To achieve a better precipitation data set, the study proposes cokriging method, a blending algorithm, to yield the blended satellite-gauge gridded rainfall at approximately 10-km resolution. The Global Satellite Mapping of Precipitation (GSMaP, 0.1⁰×0.1⁰) and daily rainfall observations from gauge stations are used. The blended product is compared with satellite data by cross-validation method. The newly-yield blended product is then utilized to re-calibrate the hydrological model. Several scenarios are simulated by the hydrological models calibrated by gauge observations alone and blended product. The performance of two calibrated hydrological models is then assessed and compared based on simulated and observed runoff.

An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing

Satellite remote sensing of ocean colour is the only method currently available for synoptically measuring wide-area properties of ocean ecosystems, such as phytoplankton chlorophyll biomass. Recently, a variety of bio-optical and ecological methods have been established that use satellite data to identify and differentiate between either phytoplankton functional types (PFTs) or phytoplankton size classes (PSCs). In this study, several of these techniques were evaluated against in situ observations to determine their ability to detect dominant phytoplankton size classes (micro-, nano- and picoplankton). The techniques are applied to a 10-year ocean-colour data series from the SeaWiFS satellite sensor and compared with in situ data (6504 samples) from a variety of locations in the global ocean. Results show that spectral-response, ecological and abundance-based approaches can all perform with similar accuracy. Detection of microplankton and picoplankton were generally better than detection of nanoplankton. Abundance-based approaches were shown to provide better spatial retrieval of PSCs. Individual model performance varied according to PSC, input satellite data sources and in situ validation data types. Uncertainty in the comparison procedure and data sources was considered. Improved availability of in situ observations would aid ongoing research in this field. (C) 2010 Elsevier B.V. All rights reserved.

Application of the GPS system for preliminary satellite orbit determination

In this paper, we discuss a method of preliminary orbit determination for an artificial satellite based on the navigation message of the GPS constellation. Orbital elements are considered as state variables and a simple dynamic model, based on the classic two-body problem, is used. The observations are formed by range and range and range-rate with respect to four visible GPS. A discrete Kalman filter with simulated data is used as filtering technique. The data are obtained through numerical propagation (Cowell's method), which considers special perturbations for the GPS satellite constellation and a user satellite. © 1997 COSPAR. Published by Elsevier Science Ltd.

Combined characterisation of GOME and TOMS total ozone measurements from space using ground-based observations from the NDSC

Several years of total ozone measured from space by the ERS-2 GOME, the Earth Probe TOMS, and the ADEOS TOMS, are compared with high-quality ground-based observations associated with the Network for the Detection of Stratospheric Change (NDSC), over an extended latitude range and a variety of geophysical conditions. The comparisons with each spaceborne sensor are combined altogether for investigating their respective solar zenith angle (SZA) dependence, dispersion, and difference of sensitivity. The space- and ground-based data are found to agree within a few percent on average. However, the analysis highlights for both GOME and TOMS several sources of discrepancies: (i) a SZA dependence with TOMS beyond 80° SZA; (ii) a seasonal SZA dependence with GOME beyond 70° SZA; (iii) a difference of sensitivity with GOME at high latitudes; (iv) a difference of sensitivity to low ozone values between satellite and SAOZ sensors around the southern tropics; (v) a north/south difference of TOMS with the ground-based observations; and (vi) internal inconsistencies in GOME total ozone. © 2001 COSPAR. Published by Elsevier Science Ltd. All rights reserved.

Ten years of NO2 comparisons between ground-based SAOZ and satellite instruments (GOME, SCIAMACHY, OMI)

SAOZ (Systeme d'Analyse par Observations Zenithales) is a ground-based UV-Visible zenith-sky spectrometer installed between 1988 and 1995 at a number of NDSC stations at various latitudes on the globe. The instrument is providing ozone and NO2 vertical columns at sunrise and sunset using the Differential Optical Absorption Spectroscopy (DOAS) technique in the visible spectral range. The ERS-2 GOME Ozone Monitoring Experiment (GOME) in 1995 was the first satellite mission to provide a global picture of atmospheric NO 2 with reasonable spatial and temporal resolution. It was then followed by SCanning ImAging spectroMeter for Atmospheric ChartographY (SCIAMACHY) onboard ENVISAT in 2002, and Ozone Monitoring Instrument (OMI) onboard EOS-AURA in 2004, with a similar capacity to monitor total NO 2. All these instruments are nadir viewing mapping spectrometers, applying the DOAS technique in the visible for deriving the NO2 total column. Here we present the results of NO2 long-term comparisons between GOME and SAOZ for the whole period of GOME operation since 1995 at all latitudes - tropics, mid-latitudes and polar regions - in both hemispheres. Comparisons are also shown with the most recently available SCIAMACHY and OMI data in 2004-2005. Overall, the daytime satellite measurements (around noon) are found consistent with sunrise ground-based data, with an average smaller difference at the tropics and mid-latitudes than in the polar areas in the summer. The agreement is even improved after correcting for the NO2 photochemical change between sunrise and the satellite overpass using a box model. However, some seasonal dependence of the difference between ground-based and satellite total NO2 still remains, related to the accuracy of photochemical simulations and the set of NO2 air mass factors used in the retrievals of both systems.

Strain rates estimated by geodetic observations in the Borborema Province, Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A unified solution to the small scale problems of the Lambda CDM model II: introducing parent-satellite interaction

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

Development of oil spill detection techniques for satellite optical sensors and their application to monitor oil spill discharge in Mediterranean sea

Satellite remote sensing has proved to be an effective support in timely detection and monitoring of marine oil pollution, mainly due to illegal ship discharges. In this context, we have developed a new methodology and technique for optical oil spill detection, which make use of MODIS L2 and MERIS L1B satellite top of atmosphere (TOA) reflectance imagery, for the first time in a highly automated way. The main idea was combining wide swaths and short revisit times of optical sensors with SAR observations, generally used in oil spill monitoring. This arises from the necessity to overcome the SAR reduced coverage and long revisit time of the monitoring area. This can be done now, given the MODIS and MERIS higher spatial resolution with respect to older sensors (250-300 m vs. 1 km), which consents the identification of smaller spills deriving from illicit discharge at sea. The procedure to obtain identifiable spills in optical reflectance images involves removal of oceanic and atmospheric natural variability, in order to enhance oil-water contrast; image clustering, which purpose is to segment the oil spill eventually presents in the image; finally, the application of a set of criteria for the elimination of those features which look like spills (look-alikes). The final result is a classification of oil spill candidate regions by means of a score based on the above criteria.

Satellite and in situ data integrated analysis to study the upper ocean an coastal environment of the Italian seas

The thesis objectives are to develop new methodologies for study of the space and time variability of Italian upper ocean ecosystem through the combined use of multi-sensors satellite data and in situ observations and to identify the capability and limits of remote sensing observations to monitor the marine state at short and long time scales. Three oceanographic basins have been selected and subjected to different types of analyses. The first region is the Tyrrhenian Sea where a comparative analysis of altimetry and lagrangian measurements was carried out to study the surface circulation. The results allowed to deepen the knowledge of the Tyrrhenian Sea surface dynamics and its variability and to defined the limitations of satellite altimetry measurements to detect small scale marine circulation features. Channel of Sicily study aimed to identify the spatial-temporal variability of phytoplankton biomass and to understand the impact of the upper ocean circulation on the marine ecosystem. An combined analysis of the satellite of long term time series of chlorophyll, Sea Surface Temperature and Sea Level field data was applied. The results allowed to identify the key role of the Atlantic water inflow in modulating the seasonal variability of the phytoplankton biomass in the region. Finally, Italian coastal marine system was studied with the objective to explore the potential capability of Ocean Color data in detecting chlorophyll trend in coastal areas. The most appropriated methodology to detect long term environmental changes was defined through intercomparison of chlorophyll trends detected by in situ and satellite. Then, Italian coastal areas subject to eutrophication problems were identified. This work has demonstrated that satellites data constitute an unique opportunity to define the features and forcing influencing the upper ocean ecosystems dynamics and can be used also to monitor environmental variables capable of influencing phytoplankton productivity.

Sea level trends in the Mediterranean from tide gauges and satellite altimetry

Sea level variation is one of the parameters directly related to climate change. Monitoring sea level rise is an important scientific issue since many populated areas of the world and megacities are located in low-lying regions. At present, sea level is measured by means of two techniques: the tide gauges and the satellite radar altimetry. Tide gauges measure sea-level relatively to a ground benchmark, hence, their measurements are directly affected by vertical ground motions. Satellite radar altimetry measures sea-level relative to a geocentric reference and are not affected by vertical land motions. In this study, the linear relative sea level trends of 35 tide gauge stations distributed across the Mediterranean Sea have been computed over the period 1993-2014. In order to extract the real sea-level variation, the vertical land motion has been estimated using the observations of available GPS stations and removed from the tide gauges records. These GPS-corrected trends have then been compared with satellite altimetry measurements over the same time interval (AVISO data set). A further comparison has been performed, over the period 1993-2013, using the CCI satellite altimetry data set which has been generated using an updated modeling. The absolute sea level trends obtained from satellite altimetry and GPS-corrected tide gauge data are mostly consistent, meaning that GPS data have provided reliable corrections for most of the sites. The trend values range between +2.5 and +4 mm/yr almost everywhere in the Mediterranean area, the largest trends were found in the Northern Adriatic Sea and in the Aegean. These results are in agreement with estimates of the global mean sea level rise over the last two decades. Where GPS data were not available, information on the vertical land motion deduced from the differences between absolute and relative trends are in agreement with the results of other studies.