Centre Regional Climate Research Articles

The Regional Climate Center Program—Past, Present, and Future: Reflections from 40 Years of Regional Climate Services

Abstract Since its inception in 1983, NOAA’s Regional Climate Center (RCC) Program has been providing timely, customized climate services for decision making across all climate-sensitive sectors. Through this 40-yr period, the RCC Program has not only seen but also has played an active role in, the evolution of climate services from the days of climate data libraries—where books of data were consulted to fulfill simple data requests—to coproduced tools that can calculate sectoral-specific, on-the-fly climate analyses in a matter of seconds. With new technologies emerging, the RCC Program is poised to build on its reputation as a trusted climate service provider by incorporating advanced methods for climate service delivery to continue to meet the needs of the nation. This publication will provide a look back at the evolution of regional climate services over the past 40 years, along with a vision for the future.

Decadal prediction centers prepare for a major volcanic eruption

Abstract The World Meteorological Organization’s Lead Centre for Annual-to-Decadal Climate prediction issues operational forecasts annually as guidance for regional climate centers, climate outlook forums and national meteorological and hydrological services. The occurrence of a large volcanic eruption such as that of Mount Pinatubo in 1991, however, would invalidate these forecasts and prompt producers to modify their predictions. To assist and prepare decadal prediction centers for this eventuality, the Volcanic Response activities under the World Climate Research Programme’s Stratosphere-troposphere Processes And their Role in Climate (SPARC) and the Decadal Climate Prediction Project (DCPP) organized a community exercise to respond to a hypothetical large eruption occurring in April 2022. As part of this exercise, the Easy Volcanic Aerosol forcing generator was used to provide stratospheric sulfate aerosol optical properties customized to the configurations of individual decadal prediction models. Participating centers then reran forecasts for 2022-2026 from their original initialization dates, and in most cases also from just before the eruption at the beginning of April 2022, according to two candidate response protocols. This article describes various aspects of this SPARC/DCPP Volcanic Response Readiness Exercise (VolRes-RE), including the hypothesized volcanic event, the modified forecasts under the two protocols from the eight contributing centers, the lessons learned during the coordination and execution of this exercise, and the recommendations to the decadal prediction community for the response to an actual eruption.

Abstract P469: Ambient Weather is Associated With Sleep and Activity in Rural South

Background: Physical activity and sleep are two of the Life’s Essential 8 steps for a healthy lifestyle and prevention of cardiovascular disease. The role of weather on an individual’s ability to meet physical activity and sleep goals is unknown. This is relevant in rural settings where the risk of cardiovascular disease is disproportionately high and extreme weather patterns are common. Objective: To investigate the association between local weather conditions and physical activity and sleep, as measured by Fitbit devices among participants in rural Alabama. Methods: Participants were enrolled from rural counties in Alabama as part of an observational study to understand cardiovascular risk in the rural Southeast. Each enrolled participant was given a Fitbit device to collect physical activity and sleep data, including total steps per day and sleep duration for six months. Weather data were obtained from a NOAA Regional Climate Center’s Applied Climate Information System for the dates each participant collected physical activity and sleep data using the participants’ zip code as location. A linear mixed effects model was used to examine the associations of daily precipitation, minimum and maximum daily ambient temperature (modeled as tertiles), BMI, gender, and age with sleep duration and daily physical activity. Results: A total of 942 participants were enrolled in the subcohort from the Alabama counties and 716 (76%) received a Fitbit device. Complete data were available from 561 participants generating 63,176 study-days. The subcohort average age was 48.8 with average BMI of 36.0 Kg/m 2 , 70% (n =660) female, and 78.7% (n = 751) Black. On average, women slept 29.1 more minutes every night (p< 0.001) but recorded 1,225 fewer steps (p <0.001) in comparison to men. An increase in BMI (1 Kg/m 2 increment) was associated with lesser sleep duration (0.98 minutes; p = 0.02) and lower daily step count (70.5, p <0.001). After adjusting for confounders, the upper tertile of ambient daily maximum temperature was associated with lesser sleep duration (5.3 minutes, p<0.001) and physical activity (218 steps, p < 0.001) in comparison to the middle tertile (referent). Conversely lowest tertile of ambient daily maximum temperature was associated with longer sleep duration (5.7 minutes, p=0.003) but not physical activity (22.0 steps, p = 0.71). An increase of an inch of ambient daily precipitation was not significantly associated with sleep duration (p=.49) but was associated with decreased physical activity (251 steps p <0.001). Conclusions: In our cross-sectional study, local temperature and precipitation were associated with lesser sleep duration and physical activity. Further analyses are warranted to understand patterns of these associations and the identification of factors that exacerbate or mitigate these weather-related associations may inform clinical practices and research direction.

The Development and Accuracy Assessment of Wet Bulb Globe Temperature Forecasts

Abstract Heat is the leading cause of weather-related death in the United States. Wet bulb globe temperature (WBGT) is a heat stress index commonly used among active populations for activity modification, such as outdoor workers and athletes. Despite widespread use globally, WBGT forecasts have been uncommon in the United States until recent years. This research assesses the accuracy of WBGT forecasts developed by NOAA’s Southeast Regional Climate Center (SERCC) and the Carolinas Integrated Sciences and Assessments (CISA). It also details efforts to refine the forecast by accounting for the impact of surface roughness on wind using satellite imagery. Comparisons are made between the SERCC/CISA WBGT forecast and a WBGT forecast modeled after NWS methods. Additionally, both of these forecasts are compared with in situ WBGT measurements (during the summers of 2019–21) and estimates from weather stations to assess forecast accuracy. The SERCC/CISA WBGT forecast was within 0.6°C of observations on average and showed less bias than the forecast based on NWS methods across North Carolina. Importantly, the SERCC/CISA WBGT forecast was more accurate for the most dangerous conditions (WBGT > 31°C), although this resulted in higher false alarms for these extreme conditions compared to the NWS method. In particular, this work improved the forecast for sites more sheltered from wind by better accounting for the influences of land cover on 2-m wind speed. Accurate forecasts are more challenging for sites with complex microclimates. Thus, appropriate caution is necessary when interpreting forecasts and onsite, real-time WBGT measurements remain critical. Significance Statement This research assesses the accuracy of wet bulb globe temperature (WBGT) forecasts. WBGT is a heat stress index that accounts for impacts of air temperature, humidity, wind, and radiation. It is widely used in occupational, athletic, and military settings for heat stress assessment, yet WBGT forecasting in the United States is a relatively new development. These forecasts can be used by decision-makers to better plan activities. We found that WBGT forecasts by NOAA’s Southeast Regional Climate Center and Carolinas Integrated Sciences and Assessments were within 0.6°C of observations overall in North Carolina and less biased than forecasts based on methods used by the U.S. National Weather Service, which had larger, colder biases that present potential safety issues in planning.

Evaluation on the Forecast Skills of Precipitation and Its Influencing Factors in the Flood Season in Liaoning Province of China

To clarify the precipitation forecast skills of climate forecast operations in the flood season in Liaoning Province of China, this study examines the forecast accuracies of China’s national and provincial operational climate prediction products and the self-developed objective prediction methods and climate model products by Shenyang Regional Climate Center (SRCC) in the flood season in Liaoning. Furthermore, the forecast accuracies of the main influencing factors on the precipitation in the flood season of Liaoning are assessed. The results show that the SRCC objective methods have a relatively high accuracy. The European Centre for Medium-Range Weather Forecasts (ECMWF) sub-seasonal forecast initialized at the sub-nearest time has the best performance in June. The National Climate Center (NCC) Climate System Model sub-seasonal forecast initialized at the sub-nearest time, and the ECMWF seasonal and sub-seasonal forecasts initialized at the nearest time, perform the best in July. The NCC sub-seasonal forecast initialized at the sub-nearest time has the best performance in August. For the accuracy of the SRCC objective method, the more significant the equatorial Middle East Pacific sea surface temperature (SST) anomaly is, the higher the evaluation score of the dynamic–analogue correction method is. The more significant the North Atlantic SST tripole is, the higher the score of the hybrid downscaling method is. For the forecast accuracy of the main influencing factors of precipitation, the tropical Atlantic SST and the north–south anti-phase SST in the northwest Pacific can well predict the locations of the southern vortex and the northern vortex in early summer, respectively. The warm (clod) SST in China offshore has a good forecast performance on the weak (strong) southerly wind in midsummer in Northeast China. The accuracy of using the SST in the Nino 1+2 areas to predict the north–south location of the western Pacific subtropical high is better than that of using Kuroshio SST. The accuracy of predicting northward-moving typhoons from July to September by using the SST in the west-wind-drift area is better than using the SST in the Nino 3 area. The above conclusions are of great significance for improving the short-term climate prediction in Liaoning.

Public health applications of historical smoke forecasts: An evaluation of archived BlueSky data for the coterminous United States, 2015–2018

BackgroundWildfires are increasing in magnitude, frequency, and severity. Populations in the wildland-urban interface and in downwind communities are at increased risk of exposure to elevated concentrations of fine particulate matter (PM2.5) and other harmful components of wildfire smoke. We conducted this analysis to evaluate the use of modeled predictions of wildfire smoke to create county-level measures of smoke exposure for public health research and surveillance. MethodsWe evaluated four years (2015–2018) of grid-based North American Mesoscale (NAM)-derived PM2.5 forecasts from the U.S. Forest Service BlueSky modeling framework with monitoring data from the Environmental Protection Agency Air Quality System (AQS), the Interagency Monitoring of Protected Visual Environments (IMPROVE), the Western Regional Climate Center (WRCC), and the Interagency Real Time Smoke Monitoring (AIRSIS) programs. To assess relationships between model-derived estimates and monitor-based observations, we assessed Spearman's correlations by spatial (i.e., county, level of urbanization, states in the western United States impacted by major wildfires, and climate regions) and temporal (i.e., month and wildfire activity periods) characteristics. We then generated county-level smoke estimates and examined spatial and temporal patterns in total and person-days of smoke exposure. ResultsAcross all counties in the coterminous United States and for all days, the correlation between county-level model- and monitor-derived PM2.5 estimates was 0.14 (p < 0.001). Correlations were stronger using data from temporary monitors and for areas and days impacted by high wildfire smoke, especially in the western United States. Correlations between county-level model- and monitor-derived estimates in non-metropolitan counties, and at higher concentrations ranged from 0.25 to 0.54 (p < 0.001). ConclusionsIn general, public health practitioners and health researchers need to consider the pros and cons associated with modeled data products for conducting health analyses. Our results support the use of model-derived smoke estimates to identify communities impacted by heavy smoke events, especially during emergency response and for communities located near wildfire episodes.

The Relationship Between Temperature and Temporal Patterns and Incidence of Abusive Head Trauma in a Midwest Region Hospital.

Background: Abusive head trauma (AHT) is a leading cause of death and disability in children and one of the most lethal forms of child abuse. Most known risk factors for AHT pertain to the infant's caregiver and limited research has assessed external influences beyond the familial or caregiver/infant dyad. Objective: Our primary objective was to determine if temperature patterns are associated with AHT events. Secondary outcomes included associations between AHT and specific days of the week, months, or seasons. Methods: This was a retrospective review of 198 patients under 24months old who were diagnosed with AHT at Saint Louis Children's Hospital. Demographic information was obtained from the medical record for each patient. For each AHT incident, the date and zip code of the incident were recorded. Temperature on the date of incident was identified using the Midwestern Regional Climate Center (MRCC). Chi square tests were utilized to calculate differences in cases per year as well as temperature and seasonal variation. Results: Temperature was not associated with a statistically significant increase in cases of AHT. There was an increase in cases as temperatures rose, but no statistically significant associations between incidence of AHT and day of the week, month, or season. Conclusion: Our study suggests no significant association between AHT incidence and temperature or temporal patterns in this Midwest hospital.

Examining patterns and drivers of variability in playa water status on the High Plains of western Kansas, 2016–2019

Playa wetlands are widely distributed across the High Plains of the central United States, providing a range of ecosystem services, such as groundwater recharge, surface water storage, and wetland habitat. Although playas are essential resources, few studies have examined the variability and controls on playa water storage. The purpose of this project is to determine how playa and watershed morphology, watershed land cover, and precipitation patterns affect timing and duration of water storage in playas. This project focuses on 92 playas distributed throughout a 10-county region in western Kansas.&#x0D; Playa and watershed morphology were calculated in a GIS environment and classified into quartiles based on playa and watershed surface area. Watershed tilled index (i.e., percent cropland versus grassland) was determined using 2016, 2017, 2018, and 2019 Cropland Data Layers available from the National Agricultural Statistics Service and classified as either cropland (more than 75% cropland), grassland (more than 75% grassland), or mixed. Monthly precipitation data for 2016–2019 were compiled from the Oakley 22S High Plains Regional Climate Center weather station. Playa water status for 2016–2019 was classified monthly as either standing water or dry (i.e., no visible standing water) by visually examining four-band satellite imagery with 3.7 m resolution available from Planet Explorer (www.planet.com).&#x0D; Playa water status is influenced by a combination of factors, including playa and watershed morphology, watershed land cover, and precipitation patterns. Larger playas have larger watersheds and standing water more frequently and for longer periods than smaller playas. Playas in cropland watersheds store water more frequently and for longer periods than playas in grassland watersheds, though differences are not statistically significant. Standing water within playas is positively correlated with monthly precipitation and reflects a short-term response to precipitation patterns, regardless of playa size or watershed land cover. The strongest controls on playa water status are playa area, monthly precipitation, and watershed area.&#x0D; Playas are critical resources for the High Plains, providing a range of ecosystem services that are dependent upon the playa’s ability to store water. Playa functions are under continued threat from cropland expansion, climate change, and playa and watershed modifications. To sustain playa functions in Kansas, efforts should focus on conserving larger grassland playas and reducing sediment inputs to playas in cropland watersheds.

The WMO RA VI RCC Network and Results from the RCC Users Forum 2020

The WMO RA VI Regional Climate Centre (RCC) is organized as a Network with dislocated functions. This is a challenge for communication among the contributing institutions. It therefore had been agreed to hold RCC Network Workshops/ Users Forums and RCC Coordination Meetings at least every four years. The latest RCC Users Forum and the Coordination Meeting have been held on 20-22 and 29 October 2020, respectively, both as virtual meetings, due to the COVID-19 pandemic. This first time virtual event allowed for participation by up to 81 representatives from NMHSs and WMO, and identifies 36 activities to be implemented in order to improve RCC Network performance and services to its end users, the NMHSs in the Region. Keywords: Regional Climate Centre Network, RAVI, User Forum, climate services, network performance

Arctic Regional Climate Centre Network (ArcRCC-N) and Arctic Climate Forum (ACF)

The ArcRCC-Network is unique in the current set of RCCs and RCC-Networks of WMO either in operation or being established around the world. The domain of the Arctic RCC-Network falls across three of the WMO Regional Associations (for Asia, Europe and North America). The structure for the ArcRCC-Network is on two levels: there are three sub-regional geographic domains, each of which is guided by a Node that performs all mandatory functions for the countries in its domain, and exceptionally, each node undertakes a significant cross-node mandatory function for the entire pan-Arctic domain. Since 2018 ArcRCC-Network has been organizing the Arctic Climate Forum (ACF) under support of WMO every spring (May) and fall (October). Outcomes from Arctic Climate Forum 6 (ACF-6) have been presented. Keywords: Arctic Regional Climate Centre Network, User Forum, climate services, nodes, network performance, Arctic Climate Forum, outcomes of ACF-6

Перспективы развития специализированного климатического прогнозирования

The possibility of developing specialized seasonal forecasting within the framework of the North Eurasia Climate Centre is discussed. The purpose of these forecasts is to access the impacts of significant large-scale anomalies of meteorological elements on various economic sectors for the timely informing of government services and private businesses to select optimal strategies for planning preventive measures. A brief overview of the groups of climatic risks in the context of the impacts on the socio-economic sphere is given according to the Russian and foreign bibliographic sources. Examples of the activities of some Regional Climate Centers that produce forecast information with an assessment of possible impacts of weather and climate conditions at seasonal scales on various human activities are given. Keywords: climate services, regional climate forums, weather and climate risks, North Eurasia Climate Centre

The WMO Regional Climate Centre – Provider of Climate Services for National Meteorological and Hydrological Services in Europe

The WMO Regional Climate Centre – Provider of Climate Services for National Meteorological and Hydrological Services in Europe

Suitability of Green Gram Production in Kenya under Present and Future Climate Scenarios Using Bias-Corrected Cordex RCA4 Models

Green gram is considered as one of the legumes suitable for cultivation in the Arid and Semi-Arid Lands (ASALs) of Kenya. However, climate change may alter the areas suitable for green gram production. This study sought to model green gram suitability in Kenya under present and future conditions using bias-corrected RCA4 models data. The datasets used were: maps of soil parameters extracted from Kenya Soil Survey map; present and future rainfall and temperature data from an ensemble of nine models from the Fourth Edition of the Rossby Centre (RCA4) Regional Climate Model (RCM); and altitude from the Digital elevation model (DEM) of the USGS. The maps were first reclassified into four classes of suitability as Highly Suitable (S1), Moderately Suitable (S2), Marginally Suitable (S3), and Not Suitable (N). The classes represent the different levels of influence of a factor on the growth and yield of green grams. The reclassified maps were then assigned a weight generated using the Analytical Hierarchy Process (AHP). A weighted overlay of climate characteristics (past and future rainfall and temperature), soil properties (depth, pH, texture, CEC, and drainage) and altitude found most of Kenya as moderately suitable for green gram production during the March to May (MAM) and October to December (OND) seasons under the baseline, RCP 4.5 and RCP 8.5 scenarios with highly suitable areas being found in Counties like Kitui, Makueni, and West Pokot among others. During the MAM season, the area currently highly suitable for green gram production (67,842.62 km2) will increase slightly to 68,600.4 km2 (1.1%) during the RCP 4.5 and reduce to 61,307.8 km2 (−9.6%) under the RCP 8.5 scenario. During the OND season, the area currently highly suitable (49,633.4 km2) will increase under both RCP 4.5 (22.2%) and RCP 8.5 (58.5%) scenarios. This increase is as a result of favourable rainfall and temperature conditions in the future.

Enhancing ACIS Maps: Increasing Usability through a GIS Portal

AbstractSince 2003, the High Plains Regional Climate Center (HPRCC) has been producing the Applied Climate Information System (ACIS) Climate Summary Maps for users all across the country. The maps allow users to quickly and easily assess climate conditions for various time scales that range from weeks to months to years, as well as spatial scales varying from state to regional and national levels. Although popular among the climate and drought monitoring community, the maps are utilized by a number of sectors, including academia, agriculture, government, resource management, and utilities. Over the years, the HPRCC has received a number of requests from users looking to customize and enhance the ACIS Climate Summary Maps. With funding provided by the National Integrated Drought Information System (NIDIS), the Center is now able to produce and distribute GIS versions of the ACIS Climate Summary Maps. Maps in GIS formats help to meet user needs by allowing them the opportunity to create custom color scales, choose specific regions, and combine information from various sources with the data available in the mapped products. The GIS data are available via a GIS Portal and GeoServer, which are accessible from the HPRCC website.

A Call for the Evaluation of Web-Based Climate Data and Analysis Tools

AbstractResearchers are producing an ever greater number of web-based climate data and analysis tools in support of natural resource research and management. Yet the apparent absence or underreporting of evaluation in the development of these applications has raised questions as to whether, by whom, and for what they are utilized, and, relatedly, whether they meet the rationale for their development. This paper joins recent efforts to address these questions by introducing one approach to evaluation—developmental evaluation—and reporting on its use in the evaluation of the Southwest Climate and Environmental Information Collaborative (SCENIC). A web interface under development at the Western Regional Climate Center, SCENIC provides access to climate data and analysis tools to environmental scientists in support of natural resource research and management in the southwestern United States. Evaluation findings highlight subtlety in the improvements necessary for ensuring a useful and usable application that could not have been ascertained in the absence of end-user feedback. We therefore urge researchers to systematically evaluate web-based climate data and analysis tools in the interest of ensuring their usefulness, usability, and fulfillment of the proposed rationale. In so doing, we recommend that researchers test and apply established evaluation frameworks, thereby engaging end users directly in the process of application development.

Results and prospects of the climatestudies and climate service in the Arctic

Climatic studies in AARI include monitoring changes in the Arctic climate system, ascertaining their causes and predictability. The beginning was laid in the 1920s by the works of V. Yu. Wiese, who investigated the causes of the warming of the Arctic in the 1920–1930s. Monitoring continues with the organization in 1932–1934 of a network of polar stations, and the first climatic assessments were created in the 1960s. At present, climate change monitoring in the Arctic is carried out on the basis of observations on the network of hydrometeorological stations, satellite observations of sea ice, ship-based expedition observations and measurements on autonomous buoy installations in the Arctic seas and the Arctic basin. The results are presented in regular reviews of climatic and ice conditions. Recent studies have evaluated the contribution of atmospheric heat transfers in the formation of temperature changes in winter and radiation inflows in summer.A scheme for the development and enhancement of warming in the Arctic has been proposed. The tasks of climate services in the Arctic are considered on the basis of the WMO initiative on the development of climate services in the form of the Arctic Regional Climate Center – network (ArcRCC-N).

Nonlinear and delayed impacts of climate on dengue risk in Barbados: A modelling study.

BackgroundOver the last 5 years (2013–2017), the Caribbean region has faced an unprecedented crisis of co-occurring epidemics of febrile illness due to arboviruses transmitted by the Aedes sp. mosquito (dengue, chikungunya, and Zika). Since 2013, the Caribbean island of Barbados has experienced 3 dengue outbreaks, 1 chikungunya outbreak, and 1 Zika fever outbreak. Prior studies have demonstrated that climate variability influences arbovirus transmission and vector population dynamics in the region, indicating the potential to develop public health interventions using climate information. The aim of this study is to quantify the nonlinear and delayed effects of climate indicators, such as drought and extreme rainfall, on dengue risk in Barbados from 1999 to 2016.Methods and findingsDistributed lag nonlinear models (DLNMs) coupled with a hierarchal mixed-model framework were used to understand the exposure–lag–response association between dengue relative risk and key climate indicators, including the standardised precipitation index (SPI) and minimum temperature (Tmin). The model parameters were estimated in a Bayesian framework to produce probabilistic predictions of exceeding an island-specific outbreak threshold. The ability of the model to successfully detect outbreaks was assessed and compared to a baseline model, representative of standard dengue surveillance practice. Drought conditions were found to positively influence dengue relative risk at long lead times of up to 5 months, while excess rainfall increased the risk at shorter lead times between 1 and 2 months. The SPI averaged over a 6-month period (SPI-6), designed to monitor drought and extreme rainfall, better explained variations in dengue risk than monthly precipitation data measured in millimetres. Tmin was found to be a better predictor than mean and maximum temperature. Furthermore, including bidimensional exposure–lag–response functions of these indicators—rather than linear effects for individual lags—more appropriately described the climate–disease associations than traditional modelling approaches. In prediction mode, the model was successfully able to distinguish outbreaks from nonoutbreaks for most years, with an overall proportion of correct predictions (hits and correct rejections) of 86% (81%:91%) compared with 64% (58%:71%) for the baseline model. The ability of the model to predict dengue outbreaks in recent years was complicated by the lack of data on the emergence of new arboviruses, including chikungunya and Zika.ConclusionWe present a modelling approach to infer the risk of dengue outbreaks given the cumulative effect of climate variations in the months leading up to an outbreak. By combining the dengue prediction model with climate indicators, which are routinely monitored and forecasted by the Regional Climate Centre (RCC) at the Caribbean Institute for Meteorology and Hydrology (CIMH), probabilistic dengue outlooks could be included in the Caribbean Health-Climatic Bulletin, issued on a quarterly basis to provide climate-smart decision-making guidance for Caribbean health practitioners. This flexible modelling approach could be extended to model the risk of dengue and other arboviruses in the Caribbean region.

Impact of meteorological conditions and PM2.5 on the onset of acute aortic dissection in monsoonal climate.

ObjectiveTo investigate the impact of meteorological conditions and PM2.5 on the onset of acute aortic dissection in monsoonal climate.MethodsA linear regression analysis was performed in monsoonal climate epidemiological survey for a period of four years on the impact of meteorological factors (minimal temperature, mean temperature, maximal temperature, average daily surface temperature, day temperature range, relative humidity, mean wind speed, and atmospheric pressure) and PM2.5 concentration on the daily incidences of acute aortic dissections. Meteorological variables and PM2.5 concentration were retrieved on a daily basis from Beijing Regional Climate Center and the Ministry of Environmental Protection of the People's Republic of China's website, and the daily incidences of acute aortic dissections were retrieved from the Clinical Data Analysis and Reporting System in the Emergency and Critical Care Center of Beijing Anzhen Hospital.ResultsDuring the study period (from January 2011 to December 2014), 1164 patients were identified as having acute aortic dissections. The corresponding incidences in spring and autumn were 0.96 and 1.00, respectively, which significantly higher than that in summer and winter. The incidences of acute aortic dissection in a day could be predicted by diurnal temperature range (DTR) using the following linear multiple regression models: incidences of acute aortic dissection = 0.543 + 0.025 × DTR.ConclusionThis is the first study to show an attributable effect of DTR on acute aortic events in monsoonal climate. Our study confirms that meteorological variables were important factors influencing the incidence of acute aortic dissection.

Establishing Best Practices to Improve Usefulness and Usability of Web Interfaces Providing Atmospheric Data

Abstract Accessing scientific data and information through an online portal can be a frustrating task, often because of the fact that they were not built with the user’s needs in mind. The concept of making web interfaces easy to use, known as “usability,” has been thoroughly researched in the field of e-commerce but has not been explicitly addressed in the atmospheric and most other sciences. As more observation stations are installed, satellites flown, models run, and field campaigns performed, data are continuously produced. Portals on the Internet have become the favored mechanisms for sharing this information and are ever increasing in number. Portals are often created without being explicitly tested for usability with the target audience though the expenses of testing are low and the returns high. To remain competitive and relevant in the provision of atmospheric information, it is imperative that developers understand design elements of a successful portal to make their product stand out among others. This work informs the audience of the benefits and basic principles of usability that can be applied to web pages presenting atmospheric information. We will also share some of the best practices and recommendations we have formulated from the results of usability testing performed on a data provision site designed for researchers in the Southwest Climate Science Center and hosted by the Western Regional Climate Center.

Climate variability and its impacts on runoff in the Kosasthaliyar sub-basin, India

&lt;p&gt;Research on the effect of climate variability/climate change on rainfall-runoff modeling is limited in humid tropical regions. Climate change has implications beyond the water resources sector, such as effects on agriculture and fisheries. Hence, such studies are becoming increasingly important. This study uses both historical data acquired in the field and future climate forecasts from General Circulation Model Hadley Centre Coupled Model, version 3 GCM HadCM3. These data are further downscaled using third generation of the Hadley Centre's regional climate model (HadRM3), with Providing REgional Climates for Impacts Studies (PRECIS) software under the three Quantifying Uncertainties in Model Projections (QUMPs). A horizontal resolution of 25 km X 25 km is used by the Centre for Climate Change and Adaptation Research, Anna University Chennai, for the state of Tamil Nadu. These downscaled data are used to study runoff changes due to climate change for the Kosasthaliyar sub-basin in South India. A trend analysis of the hydro-meteorological data for the sub-basin indicates that future rainfall is expected to decrease by approximately 10%, while the mean temperatures will increase by the year 2100. The runoff changes from 2011 to 2040 do not differ from those of the historical period of 1971 to 2000. This study is one of the first attempts to provide information on climate variability and its impacts on runoff in the Kosasthaliyar sub-basin.&lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt;Resumen&lt;/strong&gt;&lt;/p&gt;&lt;div class="page" title="Page 1"&gt;&lt;div class="section"&gt;&lt;div class="layoutArea"&gt;&lt;div class="column"&gt;&lt;p&gt;&lt;span&gt;La investigación del efecto variabilidad climática/cambio climático en el modelo pluviosidad/escorrentía es limitada en regiones tropicales húmedas, donde el cambio climático tiene implicaciones tanto en los recursos acuíferos, como &lt;/span&gt;&lt;span&gt;en la agricultura y la pesca. Por lo tanto este tipo de estudios han incrementado su importancia. Este estudio utiliza tanto los datos adquiridos en este campo como las predicciones climáticas del Modelo General de Circulación de la Célula de Hadley, en su versión 3GCM HadCM3. Estos datos fueron reducidos luego al utilizar la tercera generación del modelo climático regional del Centro Hadley (HadRM3), con el programa de Estipulación de Climas Regionales para Estudios de Impacto (PRECIS, en inglés), bajo los tres modelos de Cuantificación de la Incertidumbre en Proyecciones (QUMPs, en inglés). El Centro para el Cambio Climático y la Investigación de Adaptación de la Universidad Anna, de Chennai, en el estado Tamil Nadu, utiliza una escala horizontal de 25 kilómetros por 25 kilómetros. Esta reducción de datos se utiliza para estudiar los cambios de escorrentía por el cambio climático en la subcuenca de Kosasthaliyar, al sur de la India. Un análisis de tendencia de los datos hidrometeorológicos en la subcuenca indica que en el futuro la pluviosidad caerá en un 10 %, mientras que la temperatura media se incrementará para el año 2100. Los cambios de escorrentía para el período 2011-2040 no difieren de los del período 1971-2000. Este estudio es uno de los primeros acercamientos para proveer información sobre la variabilidad climática y sus &lt;/span&gt;&lt;span&gt;impactos en la escorrentía de la subcuenca de Khosastaliyar. &lt;/span&gt;&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;