A. Merino

Evaluation of Monthly Satellite-Derived Precipitation Products over East Africa

AbstractEast Africa experienced in the 2001–11 time period some of the worst drought events to date, culminating in the high-impact drought of 2010/11. Long-term monitoring of precipitation is thus essential, and satellite-based precipitation products can help in coping with the relatively sparse rain gauge ground networks of this area of the world. However, the complex topography and the marked geographic variability of precipitation in the region make precipitation retrieval from satellites problematic and product validation and intercomparison necessary. Six state-of-the-art monthly satellite precipitation products over East Africa during the 2001–09 time frame are evaluated. Eight areas (clusters) are identified by investigating the precipitation seasonality through the Global Precipitation Climatology Centre (GPCC) climatological gauge data. Seasonality was fully reproduced by satellite data in each of the GPCC-identified clusters. Not surprisingly, complex terrain (mountain regions in particular) re...

Weather features associated with aircraft icing conditions: a case study.

In the context of aviation weather hazards, the study of aircraft icing is very important because of several accidents attributed to it over recent decades. On February 1, 2012, an unusual meteorological situation caused severe icing of a C-212-200, an aircraft used during winter 2011-2012 to study winter cloud systems in the Guadarrama Mountains of the central Iberian Peninsula. Observations in this case were from a MP-3000A microwave radiometric profiler, which acquired atmospheric temperature and humidity profiles continuously every 2.5 minutes. A Cloud Aerosol and Precipitation Spectrometer (CAPS) was also used to study cloud hydrometeors. Finally, ice nuclei concentration was measured in an isothermal cloud chamber, with the goal of calculating concentrations in the study area. Synoptic and mesoscale meteorological conditions were analysed using the Weather Research and Forecasting (WRF) model. It was demonstrated that topography influenced generation of a mesolow and gravity waves on the lee side of the orographic barrier, in the region where the aircraft experienced icing. Other factors such as moisture, wind direction, temperature, atmospheric stability, and wind shear were decisive in the appearance of icing. This study indicates that icing conditions may arise locally, even when the synoptic situation does not indicate any risk.

Numerical simulations of snowfall events: Sensitivity analysis of physical parameterizations

Accurate estimation of snowfall episodes several hours or even days in advance is essential to minimize risks to transport and other human activities. Every year, these episodes cause severe traffic problems on the northwestern Iberian Peninsula. In order to analyze the influence of different parameterization schemes, 15 snowfall days were analyzed with the Weather Research and Forecasting (WRF) model, defining three nested domains with resolutions of 27, 9, and 3 km. We implemented four microphysical parameterizations (WRF Single-Moment 6-class scheme, Goddard, Thompson, and Morrison) and two planetary boundary layer schemes (Yonsei University and Mellor-Yamada-Janjic), yielding eight distinct combinations. To validate model estimates, a network of 97 precipitation gauges was used, together with dichotomous data of snowfall presence/absence from snowplow requests to the emergency service of Spain and observatories of the Spanish Meteorological Agency. The results indicate that the most accurate setting of WRF for the study area was that using the Thompson microphysical parameterization and Mellor-Yamada-Janjic scheme, although the Thompson and Yonsei University combination had greater accuracy in determining the temporal distribution of precipitation over 1 day. Combining the eight deterministic members in an ensemble average improved results considerably. Further, the root mean square difference decreased markedly using a multiple linear regression as postprocessing. In addition, our method was able to provide mean ensemble precipitation and maximum expected precipitation,which can be very useful in the management of water resources. Finally, we developed an application that allows determination of the risk of snowfall above a certain threshold.

Monitoring a convective winter episode of the Iberian Peninsula using a multichannel microwave radiometer

On 4 March 2011, a heavy snowfall episode affected the central Iberian Peninsula. Under the TECOAGUA Project (aimed at the study of winter cloud masses that produce snow in the Guadarrama Mountains near Madrid), measurements using a ground-based multichannel microwave radiometer (MMWR) with vertical range 10 km recorded this episode of winter convection embedded within stratiform precipitation. In contrast to radiosondes, data retrieval from the MMWR has a clear advantage for identifying hazardous weather phenomena of short duration, such as winter convective episodes. From these continuous measurements, we analyzed the behavior of variables such as temperature, surface pressure, relative humidity, liquid water content, liquid water path, water vapor content, and integrated water vapor throughout the day. The continuous measurements also permitted construction of skew-T log-P profiles every 15 min during the convective episode, indicating vertical evolution of an event with an appearance similar to a “zipper” in which temperature and dew point temperature profiles are “closed” from the surface to 400 hPa and “reopen” at the end of the event. Finally, we selected six indices of stability most suitable for the study of winter convection, namely, the Showalter index, low-topped convection index, most unstable lifted index, most unstable convective available potential energy (MUCAPE), convective inhibition, and MUCAPE level of free convection. Each of these indices has been evaluated for their capacity to warn of meteorological conditions leading to a convective heavy snowfall event.

Snowfall in the Northwest Iberian Peninsula: Synoptic Circulation Patterns and Their Influence on Snow Day Trends

In recent decades, a decrease in snowfall attributed to the effects of global warming (among other causes) has become evident. However, it is reasonable to investigate meteorological causes for such decrease, by analyzing changes in synoptic scale patterns. On the Iberian Peninsula, the Castilla y León region in the northwest consists of a central plateau surrounded by mountain ranges. This creates snowfalls that are considered both an important water resource and a transportation risk. In this work, we develop a classification of synoptic situations that produced important snowfalls at observation stations in the major cities of Castilla y León from 1960 to 2011. We used principal component analysis (PCA) and cluster techniques to define four synoptic patterns conducive to snowfall in the region. Once we confirmed homogeneity of the series and serial correlation of the snowfallday records at the stations from 1960 to 2011, we carried out a Mann-Kendall test. The results show a negative trend at most stations, so there are a decreased number of snowfall days. Finally, variations in these meteorological variables were related to changes in the frequencies of snow events belonging to each synoptic pattern favorable for snowfall production at the observatory locations.

Analysis of a seeder‐feeder and freezing drizzle event

Surface icing can cause dramatic consequences on human activities. What is more, numerical weather prediction models are not very accurate in determining freezing drizzle, which creates uncertainty when forecasting this type of weather phenomenon. Therefore, it is essential to improve the forecast accuracy of these models for such phenomena to mitigate risks caused by unforeseen freezing drizzle events. On 5 February 2012, an episode of freezing drizzle took place in the Guadarrama Mountains, at the center of the Iberian Peninsula. This episode was preceded by weak snowfall. After the freezing drizzle, moderate snowfall was recorded in the study area. This event was simulated using the Weather Research and Forecasting model. Through this analysis, we identified the meteorological factors at both synoptic scale and mesoscale that caused this episode. Wind perpendicular to an orographic barrier-generated updrafts and retention of moisture upwind, which caused orographic clouds to appear on the north side of the Guadarrama Mountains. Atmospheric stability prevented cloud formation at midlevels at the time of the freezing drizzle, which maintained cloud top temperatures warmer than −15°C during the episode. The entrance of moisture and instability at midlevels caused cloud top temperatures substantially colder than −15°C, which coincided with snow in the mountain range. Cloud top temperature and thickness control the efficiency of the glaciation process, thereby determining the type of precipitation at the surface. Freezing drizzle risk and in-cloud icing algorithms were developed with the aim of predicting similar events in the study area, which could mitigate impacts on human activities.

CLOUD TOP HEIGHT ESTIMATION FROM WRF MODEL: APPLICATION TO THE INFRARED CAMERA ONBOARD EUSO-BALLOON (CNES)

EUSO-BALLOON was launched on August 24, 2014 from Timmins (Canada) with a bispectral Infrared Camera onboard intended to measure the cloud coverage during the flight. Clouds at mid and upper levels of the Troposphere are crucial for a proper reconstruction of the main parameters of the Ultra-High Energy Cosmic Rays (UHECR).Therefore, determining Cloud Top Height (CTH) with high accuracy is crucial to estimate the effect of clouds on these measurements. With this aim, we have developed a method to extract CTH parameter via vertical profiles predicted by the Weather Research Forecast (WRF) model. Moreover, we have evaluated model ability to represent temperature and humidity profiles in different climatic regions of the globe.

Sensitivity Analysis of the WRF Model: Wind-Resource Assessment for Complex Terrain

AbstractWind energy requires accurate forecasts for adequate integration into the electric grid system. In addition, global atmospheric models are not able to simulate local winds in complex terrain, where wind farms are sometimes placed. For this reason, the use of mesoscale models is vital for estimating wind speed at wind turbine hub height. In this regard, the Weather Research and Forecasting (WRF) Model allows a user to apply different initial and boundary conditions as well as physical parameterizations. In this research, a sensitivity analysis of several physical schemes and initial and boundary conditions was performed for the Alaiz mountain range in the northern Iberian Peninsula, where several wind farms are located. Model performance was evaluated under various atmospheric stabilities and wind speeds. For validation purposes, a mast with anemometers installed at 40, 78, 90, and 118 m above ground level was used. The results indicate that performance of the Global Forecast System analysis and Eu...

Uncertainty quantification and predictability of wind speed over the Iberian Peninsula

During recent decades, the use of probabilistic forecasting methods has increased markedly. However, these predictions still need improvement in uncertainty quantification and predictability analysis. For this reason, the main aim of this paper is to develop tools for quantifying uncertainty and predictability of wind speed over the Iberian Peninsula. To achieve this goal, several spread indexes extracted from an ensemble prediction system are defined in this paper. Subsequently, these indexes were evaluated with the aim of selecting the most appropriate for the characterization of uncertainty associated to the forecasting. Selection is based on comparison of the average magnitude of ensemble spread (ES) and mean absolute percentage error (MAPE). MAPE is estimated by comparing the ensemble mean with wind speed values from different databases. Later, correlation between MAPE and ES was evaluated. Furthermore, probability distribution functions (PDFs) of spread indexes are analyzed to select the index with greater similarity to MAPE PDFs. Then, the spread index selected as optimal is used to carry out a spatiotemporal analysis of model uncertainty in wind forecasting. The results indicate that mountainous regions and the Mediterranean coast are characterized by strong uncertainty, and the spread increases more rapidly in areas affected by strong winds. Finally, a predictability index is proposed for obtaining a tool capable of providing information on whether the predictability is higher or lower than average. The applications developed may be useful in the forecasting of wind potential several days in advance, with substantial importance for estimating wind energy production.

Cloud Optical Depth obtained from the Infrared Camera data and the UV Flashers mounted on a helicopter flying under the EUSO

Spain. 2 ISDC, Astronomy Dept. University of Geneva, Switzerland. 3 University of Alabama in Huntsville (UAH), Huntsville, USA. 4 Colorado School of Mines, Golden, USA. 5 GFA. IMA. University of León, León, Spain. 6 Instituto de Astrofísica de Canarias (IAC), Vía Lactea S/N, Tenerife, Spain. 7 IDR/UPM, E. T. S. I. Aeronáutica y del Espacio, Universidad Politécnica de Madrid, Spain. 8 IFIC, CSIC, U. de València. Dpto. Física Atómica, Molecular y Nuclear, U. de València, Spain.