E. García-Ortega

Fitting an Exponential Distribution

Abstract Exponential distributions of the type N = N0 exp(−λt) occur with a high frequency in a wide range of scientific disciplines. This paper argues against a widely spread method for calculating the λ parameter in this distribution. When the ln function is applied to both members, the equation of a straight line in t is obtained, which may be fit by means of linear regression. However, the paper illustrates that this is equivalent to a least squares fit with a weight function that assigns more importance to the higher values of t. It is argued that the method of maximum likelihood should be applied, because it takes into account all of the data equally. An iterative method for determining λ is proposed, based on the method of moments for cases in which only a truncated distribution is available.

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...

Precipitation Science: Observations, Retrievals, and Modeling

Precipitation science is becoming a thrivingmultidisciplinary area as a special interest topic for meteorology, climatology, hydrology, remote sensing, and computing science. This is not surprising since precipitation features a key component of many human activities, most notably agriculture and water resources management, making rain estimation and forecasting a relevant research topic for society and policymakers. A better knowledge of precipitation processes is instrumental to respond to increasingly pressing societal needs and to provide better scientific tools for dealing with hydrological problems. This special issue gathers a number of contributions in precipitation science, including radar studies, artificial intelligence methods, modeling, geostatistical analyses, chemical research, satellite estimates, climate variability, data assimilation, computing science, solid precipitation studies, and microphysics. The synergisms between the many approaches are clear.Thus, for instance, surface precipitation is known to be a rough (i.e., not smooth) geophysical field and as such difficult to model. That makes precipitation the prime yardstick to gauge model performance. Therein, improvements in the precise quantification of rain using rain gauges, disdrometers, and satellites translate into bettermodel tuning and at the end improved model validation. The collection illustrates well the observed bloom of the studies focused on the Asian weather and climate, where a precise understanding of precipitation processes is perhaps even more important than in other geographical areas as that part of the world accounts for more than half of the planet population. Moreover, knowledge of such an important atmospheric process as the Meiyu translates into increased ability to model and simulate mesoscale systems in other parts of the planet. It is therefore worthy to pay attention to observations and simulations in that area to advance the precipitation science program: a program that could be defined as a multisource, multidisciplinary, and multinational effort to better understand precipitation physics in the context of increasing societal awareness of the consequences of ongoing global warming.

High-Resolution, Near Real-Time Simulation of Microwave Radiance Using a Simple Land-Cover Based Emissivity Prior

Satellite simulators are used to calculate the brightness temperature that would be measured by a space borne sensor under a set of atmospheric conditions accounting for the radiometric characteristics of the sensor and the orbital parameters of the satellite. In this study, a simple approach is proposed for the parameterization of emissivity over land, a key parameter for the calculation of microwave . The rationale is to simulate a large ensemble of emissivity values for each frequency and surface characteristics and then relate the most likely observed value with soil characteristics. The derived emissivity values are used for the simulation of and simulated radiance is then compared with satellite observations. It is shown that this method improves the simulation of radiance and that it is suitable to provide a first guess of the emissivity value (a prior) that can then be refined using iterative procedures.