Otto Hyvärinen

The Helsinki Testbed: A Mesoscale Measurement, Research, and Service Platform

Abstract The Finnish Meteorological Institute and Vaisala have established a mesoscale weather observational network in southern Finland. The Helsinki Testbed is an open research and quasi-operational program designed to provide new information on observing systems and strategies, mesoscale weather phenomena, urban and regional modeling, and end-user applications in a high-latitude (~60°N) coastal environment. The Helsinki Testbed and related programs feature several components: observing system design and implementation, small-scale data assimilation, nowcasting and short-range numerical weather prediction, public service, and commercial development of applications. Specifically, the observing instrumentation focuses on meteorological observations of meso-gamma-scale phenomena that are often too small to be detected adequately by traditional observing networks. In particular, more than 40 telecommunication masts (40 that are 120 m high and one that is 300 m high) are instrumented at multiple heights. Oth...

Social Media as a Source of Meteorological Observations

An increasing number of people leave their mark on the Internet by publishing personal notes (e.g., text, photos, videos) on Web-based services such as Facebook and Flickr. This creates a vast source of information that could be utilized in meteorology, for example, as a complement to traditional weather observations. Photo-sharing services offer an increasing amount of useful data, as modern mobile devices can automatically include coordinates and time stamps on photos, and users can easily tag them for content. In this study, different weather-related photos and their metadata were accessed from the photo-sharing service Flickr, and their reliability was assessed. Case studies of hail detection were then performed. The position of hail detected in the atmosphere by radar was compared with positions of Flickr photos depicting hail on the ground. As a result of this preliminary study, the authors think that further exploration of the use of Flickr photographs is warranted, and the consideration of other social media as data sources can be recommended.

Estimation of Surface Solar Global Radiation from NOAA AVHRR Data in High Latitudes

Abstract A physical method for estimating the instantaneous global irradiance and daily cumulative insolation based on Advanced Very High Resolution Radiometer data was developed and tested at high latitudes in a boreal subarctic region. The satellite estimates were compared with ground-based pyranometer measurements at six stations in Finland. From the comparison of instantaneous satellite estimates with 15-min average irradiances measured by pyranometers, a high correlation coefficient (0.97 in July 1996 and 0.99 in March 1997) between these estimates was obtained under clear-sky conditions. A standard error of 8% and a zero value of bias were obtained in both months. Under cloudy conditions the correlation coefficient in July 1996 was in the range of 0.79–0.83; in March 1997 it ranged from 0.89 to 0.96. The standard error in cloudy cases varied from 27% to 39% in July 1996 and from 17% to 33% in March 1997. For daily insolation estimates, the correlation coefficient had an average value of 0.95. The st...

New Geostationary Satellite-Based Snow-Cover Algorithm

AbstractSnow cover plays an important role in the climate system by changing the energy and mass transfer between the atmosphere and the surface. Reliable observations of the snow cover are difficult to obtain without satellites. This paper introduces a new algorithm for satellite-based snow-cover detection that is in operational use for Meteosat in the European Organisation for the Exploitation of Meteorological Satellites Satellite Application Facility on Land Surface Analysis (LSA SAF). The new version of the product is compared with the old version and the NOAA/National Environmental Satellite, Data, and Information Service Interactive Multisensor Snow and Ice Mapping System (IMS) snow-cover product. The new version of the LSA SAF snow-cover product improves the accuracy of snow detection and is comparable to the IMS product in cloud-free conditions.

A Probabilistic Derivation of Heidke Skill Score

AbstractAn alternative derivation of Heidke skill score for 2 × 2 tables is presented, starting from the assumption that a categorical forecast is useful, if the probability of an occurrence of an event, given the forecast, is greater than the base rate of the event. A tentative measure of skill would then be the difference of these probabilities, normalized by the maximum value based on the base rate. For binary events, the Heidke skill score is then the harmonic mean of these differences for both the occurrence and the nonoccurrence of the event. This derivation differs from the usual derivation in that the concept of chance agreement is not used. It is Bayesian in nature with implied updating of prior probabilities to posterior probabilities.

Comparison of Satellite Cloud Masks with Ceilometer Sky Conditions in Southern Finland

The cloud mask is an essential product derived from satellite data. Whereas cloud analysis applications typically make use of information from cloudy pixels, many other applications require cloud-free conditions. For this reason many organizations have their own cloud masks tuned to serve their particular needs. Being a fundamental product, continuous quality monitoring and validation of these cloud masks are vital. This study evaluated the performance of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Meteorological Products Extraction Facility cloud mask (MPEF), together with the Nowcasting Satellite Application Facility (SAFNWC) cloud masks provided by Meteo-France (SAFNWC/ MSG) and the Swedish Meteorological and Hydrological Institute (SAFNWC/PPS), in the high-latitude area of greater Helsinki in Finland. The first two used the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument from the geostationary Meteosat-8 satellite, whereas the last used the Advanced Very High Resolution Radiometer (AVHRR) instrument on board the polar-orbiting NOAA satellite series. Ceilometer data from the Helsinki Testbed, an extensive observation network covering the greater Helsinki area in Finland, were used as reference data in the cloud mask comparison. A computational method, called bootstrapping, is introduced to account for the strong temporal and spatial correlation of the ceilometer observations. The method also allows the calculation of the confidence intervals (CI) for the results. This study comprised data from February and August 2006. In general, the SAFNWC/MSG algorithm performed better than MPEF. Differences were found especially in the early morning low cloud detection. The SAFNWC/PPS cloud mask performed very well in August, better than geostationary-based masks, but had problems in February when its performance was worse. The use of the CIs gave the results more depth, and their use should be encouraged.

Comparison of Snow Cover from Satellite and Numerical Weather Prediction Models in the Northern Hemisphere and Northern Europe

Abstract Snow cover has a strong effect on the surface and lower atmosphere in NWP models. Because the progress of in situ observations has stalled, satellite-based snow analyses are becoming increasingly important. Currently, there exist several products that operationally map global or continental snow cover. In this study, satellite-based snow cover analyses from NOAA, NASA, and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), and NWP snow analyses from the High-Resolution Limited-Area Model (HIRLAM) and ECMWF, were compared using data from January to June 2006. Because no analyses were independent and since available in situ measurements were already used in the NWP analyses, no independent ground truth was available and only the consistency between analyses could be compared. Snow analyses from NOAA, NASA, and ECMWF were similar, but the analysis from NASA was greatly hampered by clouds. HIRLAM and EUMETSAT deviated most from other analyses. Even though the anal...

Validation of Automatic Cb Observations for METAR Messages without Ground Truth

AbstractIn aviation meteorology, METAR messages are used to disseminate the existence of cumulonimbus (Cb) clouds. METAR messages are traditionally constructed manually from human observations, but there is a growing trend toward automation of this process. At the Finnish Meteorological Institute (FMI), METAR messages incorporate an operational automatic detection of Cb based solely on weather radar data, when manual observations are not available. However, the verification of this automatic Cb detection is challenging, as good ground truth data are not often available; even human observations are not perfect as Cb clouds can be obscured by other clouds, for example. Therefore, statistical estimation of the relevant verification measures from imperfect observations using latent class analysis (LCA) was explored. In addition to radar-based products and human observations, the convective rainfall rate from EUMETSAT’s Nowcasting Satellite Application Facility and lightning products from the Finnish lightning...

Operational Snowcover Mapping using MSG/SEVIRI Data

EUMETSATs Land Surface Analysis Satellite Applications Facility (LSA SAF) has been producing daily snow cover product for two years with a baseline algorithm for the land areas covered by EUMETSATs MSG satellites SEVIRI instrument. This paper presents a new improved version of the algorithm which is currently used for operational snow cover product generation in the LSA SAF. Some examples of the product are presented and the product is compared to NOAA/NESDIS IMS snow cover product and the previous version of the LSA SAF snow cover product.

Regional Assessment of Temperature-Related Mortality in Finland

The aim of this study was to assess regional differences in temperature–mortality relationships across 21 hospital districts in Finland. The temperature dependence of the daily number of all-cause, all-aged deaths during 2000–2014 was studied in each hospital district by using daily mean temperatures, spatially averaged across each hospital district, to describe exposure to heat stress and cold stress. The relationships were modelled using distributed lag non-linear models (DLNM). In a simple model version, no delayed impacts of heat and cold on mortality were taken into account, whereas a more complex version included delayed impacts up to 25 days. A meta-analysis with selected climatic and sociodemographic covariates was conducted to study differences in the relationships between hospital districts. A pooled mortality-temperature relationship was produced to describe the average relationship in Finland. The simple DLNM model version without lag gave U-shaped dependencies of mortality on temperature almost without exception. The outputs of the model version with a 25-day lag were also U-shaped in most hospital districts. According to the meta-analysis, the differences in the temperature-mortality relationships between hospital districts were not statistically significant on the absolute temperature scale, meaning that the pooled mortality–temperature relationship can be applied to the whole country. However, on a relative temperature scale, heterogeneity was found, and the meta-regression suggested that morbidity index and population in the hospital districts might explain some of this heterogeneity. The pooled estimate for the relative risk (RR) of mortality at a daily mean temperature of 24 °C was 1.16 (95% CI 1.12–1.20) with reference at 14 °C, which is the minimum mortality temperature (MMT) of the pooled relationship. On the cold side, the RR at a daily mean temperature of −20 °C was 1.14 (95% CI 1.12–1.16). On a relative scale of daily mean temperature, the MMT was found at the 79th percentile.