Recurrence for the frog model with drift on Zd\mathbb{Z}^d

In this paper we present a recurrence criterion for the frog model on $\mathbb{Z}^d$ with an i.i.d. initial configuration of sleeping frogs and such that the underlying random walk has a drift to the right.Comment: 13 pages; problem about missing references fixed (thanks to Tal Orenshtein for letting us know!

Long-term variability of solar irradiance and its implications for photovoltaic power in West Africa

This paper addresses long-term changes in solar irradiance for West Africa (3° N to 20° N and 20° W to 16° E) and its implications for photovoltaic power systems. Here we use satellite irradiance (Surface Solar Radiation Data Set-Heliosat, Edition 2.1, SARAH-2.1) to derive photovoltaic yields. Based on 35 years of data (1983–2017) the temporal and regional variability as well as long-term trends of global and direct horizontal irradiance are analyzed. Furthermore, at four locations a detailed time series analysis is undertaken. The dry and the wet season are considered separately

Trends and Variability of Surface Solar Radiation in Europe Based On Surface- and Satellite-Based Data Records

The incoming solar radiation is the essential climate variable that determines the Earth's energy cycle and climate. As long-term high-quality surface measurements of solar radiation are rare, satellite data are used to derive more information on its spatial pattern and its temporal variability. Recently, the EUMETSAT Satellite Application on Climate Monitoring (CM SAF) has published two satellite-based climate data records: Surface Solar Radiation Data Set-Heliosat, Edition 2 (SARAH-2), and Clouds and Radiation Data Set based on AVHRR (advanced very high resolution radiometer) Satellite Measurements, Edition 2 (CLARA-A2). Both data records provide estimates of surface solar radiation. In this study, these new climate data records are compared to surface measurements in Europe during the period 1983\u20132015. SARAH-2 and CLARA-A2 show a high accuracy compared to ground-based observations (mean absolute deviations of 6.9 and 7.3 W/m2, respectively) highlighting a good agreement considering the temporal behavior and the spatial distribution. The results show an overall brightening period since the 1980s onward (comprised between 1.9 and 2.4 W/m2/decade), with substantial decadal and spatial variability. The strongest brightening is found in eastern Europe in spring. An exception is found for northern and southern Europe, where the trends shown by the station data are not completely reproduced by satellite data, especially in summer in southern Europe. We conclude that the major part of the observed trends in surface solar radiation in Europe is caused by changes in clouds and that remaining differences between the satellite- and the station-based data might be connected to changes in the direct aerosol effect and in snow cover

Satellite-based trends of solar radiation and cloud parameters in Europe

Solar radiation is the main driver of the Earth\u2019s climate. Measuring solar radiation and analysing its interaction with clouds are essential for the understanding of the climate system. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) generates satellite-based, high-quality climate data records, with a focus on the energy balance and water cycle. Here, multiple of these data records are analyzed in a common framework to assess the consistency in trends and spatio-temporal variability of surface solar radiation, top-of-atmosphere reflected solar radiation and cloud fraction. This multi-parameter analysis focuses on Europe and covers the time period from 1992 to 2015. A high correlation between these three variables has been found over Europe. An overall consistency of the climate data records reveals an increase of surface solar radiation and a decrease in top-of-atmosphere reflected radiation. In addition, those trends are confirmed by negative trends in cloud cover. This consistency documents the high quality and stability of the CM SAF climate data records, which are mostly derived independently from each other. The results of this study indicate that one of the main reasons for the positive trend in surface solar radiation since the 1990\u2019s is a decrease in cloud coverage even if an aerosol contribution cannot be completely ruled out

Evaluating satellite-based diurnal cycles of precipitation in the African tropics

Precipitation plays a major role in the energy and water cycles of the earth. Because of its variable nature, consistent observations of global precipitation are challenging. Satellite-based precipitation datasets present an alternative to in situ–based datasets in areas sparsely covered by ground stations. These datasets are a unique tool for model evaluations, but the value of satellite-based precipitation datasets depends on their application and scale. Numerous validation studies considered monthly or daily time scales, while less attention is given to subdaily scales. In this study subdaily satellite-based rainfall data are analyzed in West Africa, a region with strong diurnal variability. Several satellite-based precipitation datasets are validated, including Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), TRMM 3G68 products, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN), and Climate Prediction Center (CPC) morphing technique (CMORPH) data. As a reference, highly resolved in situ data from the African Monsoon Multidisciplinary Analysis–Couplage de l’Atmosphere Tropical et du Cycle Hydrologique (AMMA-CATCH) are used. As a result, overall the satellite products capture the diurnal cycles of precipitation and its variability as observed on the ground reasonably well. CMORPH and TMPA data show overall good results. For locally induced convective rainfall in the evening most satellite data show slight delays in peak precipitation of up to 2 h

Smart Approaches for Evaluating Photosynthetically Active Radiation at Various Stations Based on MSG Prime Satellite Imagery

Photosynthetically active radiation (PAR) is the 400–700 nm portion of the solar radiation spectrum that photoautotrophic organisms including plants, algae, and cyanobacteria use for photosynthesis. PAR is a key variable in global ecosystem and Earth system modeling, playing a prominent role in carbon and water cycling. Alongside air temperature, water availability, and atmospheric CO2 concentration, PAR controls photosynthesis and consequently biomass productivity in general. The management of agricultural and horticultural crops, forests, grasslands, and even grasses at sports venues is a non-exhaustive list of applications for which an accurate knowledge of the PAR resource is desirable. Modern agrivoltaic systems also require a good knowledge of PAR in conjunction with the variables needed to monitor the co-located photovoltaic system. In situ quality-controlled PAR sensors provide high-quality information for specific locations. However, due to associated installation and maintenance costs, such high-quality data are relatively scarce and generally extend over a restricted and sometimes non-continuous period. Numerous studies have already demonstrated the potential offered by surface radiation estimates based on satellite information as reliable alternatives to in situ measurements. The accuracy of these estimations is site-dependent and is related, for example, to the local climate, landscape, and viewing angle of the satellite. To assess the accuracy of PAR satellite models, we inter-compared 11 methods for estimating 30 min surface PAR based on satellite-derived estimations at 33 ground-based station locations over several climate regions in Europe, Africa, and South America. Averaged across stations, the results showed average relative biases (relative to the measurement mean) across methods of 1 to 20%, an average relative standard deviation of 25 to 30%, an average relative root mean square error of 25% to 35% and a correlation coefficient always above 0.95 for all methods. Improved performance was seen for all methods at relatively cloud-free sites, and quality degraded towards the edge of the Meteosat Second Generation viewing area. A good compromise between computational time, memory allocation, and performance was achieved for most locations using the Jacovides coefficient applied to the global horizontal irradiance from HelioClim-3 or the CAMS Radiation Service. In conclusion, satellite estimations can provide a reliable alternative estimation of ground-based PAR for most applications

The diurnal cycle of clouds and precipitation : an evaluation of multiple data sources

Clouds and precipitation are essential climate variables. Because of their high spatial and temporal variability, their observation and modeling is difficult. In this thesis multiple observational data sources, including satellite data and station data are globally analyzed to understand the distribution and variability of clouds and precipitation, while a special focus is on the diurnal cycle of both variables. Substantial diurnal cycles of clouds and precipitation are observed in the tropics, with different properties over land and ocean. But also in Europe cloud diurnal cycles are observed in the summer season. Overall the maximum cloud cover and also the maximum precipitation is observed in the afternoon over land, and in the morning over ocean. The analyzed climate model simulations and the model-based reanalysis fail to simulate the observed diurnal cycles. Owing to their limited resolution, models can not fully resolve the processes responsible for the existence of diurnal cycles of clouds and precipitation