scholarly journals Scientific motivation for ADM/Aeolus mission

2018 ◽  
Vol 176 ◽  
pp. 02008
Author(s):  
Erland Källén
Keyword(s):  
Weather Forecast ◽  
Weather Forecasts ◽  
Weather And Climate ◽  
Medium Range ◽  
Forecast Models ◽  
Tropical Areas ◽  
Global Coverage ◽  
Wind Lidar ◽  
Wind Profiles

The ADM/Aeolus wind lidar mission will provide a global coverage of atmospheric wind profiles. Atmospheric wind observations are required for initiating weather forecast models and for predicting and monitoring long term climate change. Improved knowledge of the global wind field is widely recognised as fundamental to advancing the understanding and prediction of weather and climate. In particular over tropical areas there is a need for better wind data leading to improved medium range (3-10 days) weather forecasts over the whole globe.

scholarly journals How Can Existing Ground-Based Profiling Instruments Improve European Weather Forecasts?

2019 ◽  
Vol 100 (4) ◽  
pp. 605-619 ◽  
Author(s):  
A. J. Illingworth ◽  
D. Cimini ◽  
A. Haefele ◽  
M. Haeffelin ◽  
M. Hervo ◽  
...  
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Positive Impact ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Time Data ◽  
Weather Forecasts ◽  
Forecast Models ◽  
Wind Lidar ◽  
Microwave Radiometers

Abstract To realize the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog, and poor air quality from high-resolution mesoscale models, the forecast models must be initialized with an accurate representation of the current state of the atmosphere, but the lowest few kilometers are hardly accessible by satellite, especially in dynamically active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real time to forecast centers. The three classes of instruments are i) automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog, and volcanic ash, the last two being especially important for air traffic control; ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind gusts, and low-level jets; and iii) microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. The project includes collaboration from 22 European countries and 15 European national weather services, which involves the implementation of common operating procedures, instrument calibrations, data formats, and retrieval algorithms. Currently, data from 265 ceilometers in 19 countries are being distributed in near–real time to national weather forecast centers; this should soon rise to many hundreds. One wind lidar is currently delivering real time data rising to 5 by the end of 2019, and the plan is to incorporate radiometers in 2020. Initial data assimilation tests indicate a positive impact of the new data.

scholarly journals Evaluating sub-seasonal heatwave reforecasts of the ECMWF over Europe

2021 ◽  
Author(s):  
Natalia Korhonen ◽  
Otto Hyvärinen ◽  
Matti Kämäräinen ◽  
Kirsti Jylhä
Keyword(s):  
Heat Wave ◽  
Heat Waves ◽  
Lead Times ◽  
Weather Forecasts ◽  
Wave Forecast ◽  
Extended Range ◽  
Hot Days ◽  
Medium Range ◽  
Summer Temperatures

<p>Severe heatwaves have harmful impacts on ecosystems and society. Early warning of heat waves help with decreasing their harmful impact. Previous research shows that the Extended Range Forecasts (ERF) of the European Centre for Medium-Range Weather Forecasts (ECMWF) have over Europe a somewhat higher reforecast skill for extreme hot summer temperatures than for long-term mean temperatures. Also it has been shown that the reforecast skill of the ERFs of the ECMWF was strongly increased by the most severe heat waves (the European heatwave 2003 and the Russian heatwave 2010).</p><p>Our aim is to be able to estimate the skill of a heat wave forecast at the time the forecast is given. For that we investigated the spatial and temporal reforecast skill of the ERFs of the ECMWF to forecast hot days (here defined as a day on which the 5 days running mean surface temperature is above its summer 90<sup>th</sup> percentile) in the continental Europe in summers 2000-2019. We used the ECMWF 2-meter temperature reforecasts and verified them against the ERA5 reanalysis. The skill of the hot day reforecasts was estimated by the symmetric extremal dependence index (SEDI) which considers both hit rates and false alarm rates of the hot day forecasts. Further, we investigated the skill of the heatwave reforecasts based on at which time steps of the forecast the hot days were forecasted. We found that on the mesoscale (horizontal scale of ~500 km) the ERFs of the ECMWF were most skillful in predicting the life cycle of a heat wave (lasting up to 25 days) about a week before its start and during its course. That is, on the mesoscale those reforecasts, in which hot day(s) were forecasted to occur during the first 7…11 days, were more skillful on lead times up to 25 days than the rest of the heat wave forecasts. This finding is valuable information, e.g., in the energy and health sectors while preparing for a coming heat wave.</p><p>The work presented here is part of the research project HEATCLIM (Heat and health in the changing climate) funded by the Academy of Finland.</p>

Trend analysis of extratropical cyclones in long-term ERA5 data series (1950-2019)

2021 ◽  
Author(s):  
Richard Blender ◽  
Alexia Karwat ◽  
Christian Franzke
Keyword(s):  
Nearest Neighbor ◽  
Climate Extremes ◽  
Reanalysis Data ◽  
Nearest Neighbor Search ◽  
Data Series ◽  
Extratropical Cyclones ◽  
Weather Forecasts ◽  
Neighbor Search ◽  
Weather And Climate

<p>Extratropical cyclones are the primary natural hazards affecting Europe. With the release of ERA5 reanalysis data from 1950-1978 by the European Centre for Medium-Range Weather Forecasts (ECMWF), new opportunities have arisen to investigate mid-latitude cyclones in terms of climatic features and trends in longer and higher resolution. We analyze cyclones by nearest neighbor search in 1000 hPa geopotential height minima in different high resolutions for different minimum life-times. We find an intensification of North Atlantic cyclones in 1950-2019. Short-lived cyclones grow in radius and depth. In the Mediterranean, however, long-lived cyclones have weakened; but traveled also further in 1950-2019. Additionally, we illustrate relations between cyclone tracks, radii and correlated weather and climate extremes.</p>

scholarly journals IMPLEMENTASI BACKPROPAGATION NEURAL NETWORK DALAM PRAKIRAAN CUACA DI DAERAH BALI SELATAN

2016 ◽  
Vol 5 (4) ◽  
pp. 126 ◽  
Author(s):  
I MADE DWI UDAYANA PUTRA ◽  
G. K. GANDHIADI ◽  
LUH PUTU IDA HARINI
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Learning Algorithm ◽  
Weather Forecast ◽  
Weather Forecasts ◽  
Forecast Models ◽  
Artificial Neural Network Method ◽  
Artificial Neural ◽  
Hidden Layer ◽  
Backpropagation Learning

Weather information has an important role in human life in various fields, such as agriculture, marine, and aviation. The accurate weather forecasts are needed in order to improve the performance of various fields. In this study, use artificial neural network method with backpropagation learning algorithm to create a model of weather forecasting in the area of ??South Bali. The aim of this study is to determine the effect of the number of neurons in the hidden layer and to determine the level of accuracy of the method of artificial neural network with backpropagation learning algorithm in weather forecast models. Weather forecast models in this study use input of the factors that influence the weather, namely air temperature, dew point, wind speed, visibility, and barometric pressure.The results of testing the network with a different number of neurons in the hidden layer of artificial neural network method with backpropagation learning algorithms show that the increase in the number of neurons in the hidden layer is not directly proportional to the value of the accuracy of the weather forecasts, the increase in the number of neurons in the hidden layer does not necessarily increase or decrease value accuracy of weather forecasts we obtain the best accuracy rate of 51.6129% on a network model with three neurons in the hidden layer.

scholarly journals Coproducing Weather Forecast Information with and for Smallholder Farmers in Ghana: Evaluation and Design Principles

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 902
Author(s):  
Talardia Gbangou ◽  
Rebecca Sarku ◽  
Erik Van Slobbe ◽  
Fulco Ludwig ◽  
Gordana Kranjac-Berisavljevic ◽  
...  
Keyword(s):  
Smallholder Farmers ◽  
Weather Forecast ◽  
Modern Technology ◽  
Climatic Conditions ◽  
Information And Communications Technology ◽  
Small Scale ◽  
Weather Forecasts ◽  
Monitoring Tools ◽  
Weather And Climate ◽  
Small Scale Farmers

Many West African farmers are struggling to cope with changing weather and climatic conditions. This situation limits farmers’ ability to make optimal decisions for food and income security. Developing more useful and accessible weather and climate information services (WCIS) can help small-scale farmers improve their adaptive capacity. The literature suggests that such WCIS can be achieved if forecast information is produced jointly by farmers and scientists. To test this hypothesis and derive design requirements for effective WCIS, we evaluated the outcomes of an experimental coproduction of weather forecasts in Ada, Ghana. The experiment involved a user-driven design and testing of information and communications technology (ICT)-based digital (smartphones and apps) and rainfall monitoring tools by 22 farmers. They collected data and received weather forecasts during the 2018/2019 study period. The results showed a positive evaluation of the intervention, expressed by the level of engagement, the increase in usability of the tools and understanding of forecast uncertainty, outreach capacity with other farmers, and improved daily farming decisions. The success of the intervention was attributed to the iterative design process, as well as the training, monitoring, and technical support provided. We conclude that the application of modern technology in a coproduction process with targeted training and monitoring can improve smallholder farmers’ access to and use of weather and climate forecast information.

New Methods for Data Storage of Model Output from Ensemble Simulations

2019 ◽  
Vol 147 (2) ◽  
pp. 677-689 ◽  
Author(s):  
Peter D. Düben ◽  
Martin Leutbecher ◽  
Peter Bauer
Keyword(s):  
Data Storage ◽  
Climate Modeling ◽  
Model Resolution ◽  
Ensemble Spread ◽  
Ensemble Forecasts ◽  
Weather Forecasts ◽  
Ensemble Simulations ◽  
New Methods ◽  
Weather And Climate ◽  
Medium Range

Abstract Data storage and data processing generate significant cost for weather and climate modeling centers. The volume of data that needs to be stored and data that are disseminated to end users increases with increasing model resolution and the use of larger forecast ensembles. If precision of data is reduced, cost can be reduced accordingly. In this paper, three new methods to allow a reduction in precision with minimal loss of information are suggested and tested. Two of these methods rely on the similarities between ensemble members in ensemble forecasts. Therefore, precision will be high at the beginning of forecasts when ensemble members are more similar, to provide sufficient distinction, and decrease with increasing ensemble spread. To keep precision high for predictable situations and low elsewhere appears to be a useful approach to optimize data storage in weather forecasts. All methods are tested with data of operational weather forecasts of the European Centre for Medium-Range Weather Forecasts.

scholarly journals Comprehensive evaluation of satellite-based and reanalysis soil moisture products using in situ observations over China

2021 ◽  
Author(s):  
Xiaolu Ling ◽  
Ying Huang ◽  
Weidong Guo ◽  
Yixin Wang ◽  
Chaorong Chen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Mainland China ◽  
Severe Drought ◽  
Weather Forecasts ◽  
European Centre ◽  
Drought Conditions ◽  
Medium Range

Abstract. Soil moisture (SM) plays a critical role in the water and energy cycles of the earth system; consequently, a long-term SM product with high quality is urgently needed. In this study, five SM products, including one microwave remote sensing product [European Space Agency's Climate Change Initiative (ESA CCI)] and four reanalysis datasets [European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-Interim (ERAI), National Centers for Environmental Prediction (NCEP), the Twentieth Century Reanalysis Project from National Oceanic and Atmospheric Administration (NOAA) and the European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5)], are systematically evaluated using in situ measurements during 1981–2013 in four climate regions at different timescales over mainland China. The results show that ESA CCI is closest to the observations in terms of both the spatial distributions and magnitude of the monthly SM. All reanalysis products tend to overestimate soil moisture in all regions but have higher correlations than the remote sensing product except in Northwest China. The largest inconsistency is found in southern Northeast China, with a relative RMSE value larger than 0.1. However, none of the products can well reproduce the trends of interannual anomalies. The largest relative bias of 44.6 % is found for the ERAI SM product under severe drought conditions, and the lowest relative biases of 4.7 % and 9.5 % are found for the ESA CCI SM product under severe drought conditions and the NCEP SM product under normal conditions, respectively. As decomposing mean square errors in all the products suggests that the bias terms are the dominant contribution, the ESA CCI SM product is a good option for long-term hydrometeorological applications in mainland China. ERA5 is also a promising product, which is attributed to the incorporation of more observations. This long-term intercomparison study provides clues for SM product enhancement and further hydrological applications.

One million feet view of Level-2 Processing Facility managed at European Centre for Medium-Range Weather Forecasts (ECMWF)

2020 ◽  
Author(s):  
Rakesh Prithiviraj
Keyword(s):  
Wind Profile ◽  
European Space Agency ◽  
Weather Forecast ◽  
System Perspective ◽  
Weather Forecasts ◽  
European Centre ◽  
Ground Segment ◽  
Processing Facility ◽  
Medium Range ◽  
Level 2

<p><strong>Title:</strong> One million feet view of Level-2 Processing Facility managed at European Centre for Medium-Range Weather Forecasts (ECMWF)</p><p><strong>Authors:</strong> Rakesh Prithiviraj, Ioannis Mallas, Cristiano Zanna </p><p><strong>Affiliation of authors:</strong> European Centre for Medium-Range Weather Forecasts (ECMWF)</p><p><strong>Abstract text</strong><br>Launched in August 2018, European Space Agency’s Aeolus satellite mission measures Earth's wind profile from space. The Aeolus ground segment mainly comprises of:<br>• Flight Operations Segment (FOS) to monitor and control Aeolus satellite and the instrument onboard, <br>• Payload Data Ground Segment (PDGS) for the acquisition and systematic generation of Level-1A and Level-1B products and <br>• Level-2 Processing Facility (L2PF) at ECMWF for the generation and dissemination of Level-2B and Level-2C products. </p><p>ECMWF is both a research institute and a 24/7 operational service, producing global numerical weather predictions and other data for our Member and Co-operating States and the broader community. ECMWF relies on its atmospheric model and data assimilation system which is called the Integrated Forecasting System (IFS) to make weather predictions. ECMWF has one of the largest supercomputer facilities and meteorological data archives in the world.</p><p>This talk focusses on the Aeolus L2PF facility at ECMWF providing an overview of the processing infrastructure, relevant dataflows, monitoring system and presents the technical/system perspective of Aeolus L2PF in the context of weather forecast. The L2PF facility receives L1B data from Aeolus PDGS and systematically generates and disseminates L2B products and L2C products. The centre is also responsible for the generation of meteorological auxiliary data which is one of the critical inputs for the L2B generation.  The talk also shows various components at ECMWF that work together to achieve more than 99% L2B completeness. The components include ECMWF Production Data Store (ECPDS), ECMWF's High Performance Computing Facility (HPCF) and L2PF cluster. </p><p>The talk concludes with references to tests carried out at ECMWF that have demonstrated that new wind profile observations from Aeolus satellite significantly improve weather forecasts, particularly in the southern hemisphere and the tropics. Because the positive impact of Aeolus on the weather predictions, Aeolus data is expected to be part of the operational weather forecast system at ECMWF in January 2020.</p>

scholarly journals Trajectory matching of ozonesondes and MOZAIC measurements in the UTLS – Part 2: Application to the global ozonesonde network

2014 ◽  
Vol 7 (1) ◽  
pp. 241-266 ◽  
Author(s):  
J. Staufer ◽  
J. Staehelin ◽  
R. Stübi ◽  
T. Peter ◽  
F. Tummon ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Data Sets ◽  
Wind Fields ◽  
Concentration Cell ◽  
Weather Forecasts ◽  
Long Term Stability ◽  
Medium Range ◽  
The Difference ◽  
Long Term Trend

Abstract. Both balloon-borne electrochemical ozonesondes and MOZAIC (measurements of ozone, water vapour, carbon monoxide and nitrogen oxides by in-service Airbus aircraft) provide very valuable data sets for ozone studies in the upper troposphere/lower stratosphere (UTLS). Although MOZAIC's highly accurate UV-photometers are regularly inspected and recalibrated annually, recent analyses cast some doubt on the long-term stability of their ozone analysers. To investigate this further, we perform a 16 yr comparison (1994–2009) of UTLS ozone measurements from balloon-borne ozonesondes and MOZAIC. The analysis uses fully three-dimensional trajectories computed from ERA-Interim (European Centre for Medium-Range Weather Forecasts Re-analysis) wind fields to find matches between the two measurement platforms. Although different sensor types (Brewer-Mast and Electrochemical Concentration Cell ozonesondes) were used, most of the 28 launch sites considered show considerable differences of up to 25% compared to MOZAIC in the mid-1990s, followed by a systematic tendency to smaller differences of around 5–10% in subsequent years. The reason for the difference before 1998 remains unclear, but observations from both sondes and MOZAIC require further examination to be reliable enough for use in robust long-term trend analyses starting before 1998. According to our analysis, ozonesonde measurements at tropopause altitudes appear to be rather insensitive to changing the type of the Electrochemical Concentration Cell ozonesonde, provided the cathode sensing solution strength remains unchanged. Scoresbysund (Greenland) showed systematically 5% higher readings after changing from Science Pump Corporation sondes to ENSCI Corporation sondes, while a 1.0% KI cathode electrolyte was retained.

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