Identification of Cirrus over Wausau during the 1986 FIRE IFO from ground-based radiometer data

The potential of using irradiation data to indicate episodes of cirrus cloudiness during the daylight hours is explored. Thresholds separating cirrus from other clouds and clear skies are determined using four days of irradiation data, hourly weather observations, sky photographs, sky video, and occasional lidar observations. Data were gathered during the First International Satellite Cloud Climatology Program (ISCCP) Regional Experiment (FIRE) Intensive Field Observations (IFO) cirrus project. Thresholds are tested using data from the remaining 17 days of the IFO. Cirrus episodes are defined as intervals when the sky cover is primarily cirrus. Measurements of incoming shortwave and near infrared full hemispheric and diffuse irradiation, and atmospheric infrared irradiation were made at Wausau, Wisconsin Municipal Airport. Data were collected between October 13 and November 2, 1986 and are one minute averages of ten second samples. Data from October 23 and from October 27 to 29 were used for threshold determination. Using weather observations, lidar output, photographs and video, sky conditions were grouped into three categories: noncirrus cloudy, cirrus, and clear. Irradiation data from all periods falling under each of the sky categories were then examined and thresholds denoting a change from one sky category to another were determined. Variables with only a small amount of overlap between sky categories were selected as key indicators

Impact of cirrus on the surface radiative environment at the FIRE ETLA Palisades, NY site

FIRE Extended Time Limited Area (ETLA) observations provide year round information critical to gaining a better understanding of cloud/climate interactions. The Lamont/Rutgers team has participated in the ETLS program through the collection and analysis of shortwave and longwave downwelling irradiances at Palisades, NY. These data are providing useful information on surface radiative fluxes with respect to sky condition, solar zenith angle and season. Their utility extends to the calibration and validation of cloud/radiative models and satellite cloud and radiative retrievals. The impact cirrus clouds have on the surface radiative environment is examined using Palisades ETLA information on atmospheric transmissivities and downwelling longwave fluxes for winter and summer cirrus and clear sky episodes in 1987

Contribution of Lake-Effect Snow to the Catskill Mountains Snowpack

Meltwater from snow that falls in the Catskill Mountains in southern New York contributes to reservoirs that supply drinking water to approximately nine million people in New York City. Using the NOAA National Ice Centers Interactive Multisensor Snow and Ice Mapping System (IMS) 4km snow maps, we have identified at least 32 lake-effect (LE) storms emanating from Lake Erie andor Lake Ontario that deposited snow in the CatskillDelaware Watershed in the Catskill Mountains of southern New York State between 2004 and 2017. This represents a large underestimate of the contribution of LE snow to the Catskills snowpack because many of the LE snowstorms are not visible in the IMS snow maps when they travel over snow-covered terrain. Most of the LE snowstorms that we identified originate from Lake Ontario but quite a few originate from both Erie and Ontario, and a few from Lake Erie alone. Using satellite, meteorological and reanalysis data we identify conditions that contributed to LE snowfall in the Catskills. Clear skies following some of the storms permitted measurement of the extent of snow cover in the watershed using multiple satellite sensors. IMS maps tend to overestimate the extent of snow compared to MODerate resolution Imaging Spectroradiometer (MODIS) and Landsat-derived snow-cover extent maps. Using this combination of satellite and meteorological data, we can begin to quantify the important contribution of LE snow to the Catskills Mountain snowpack. Changes that are predicted in LE snowfall from the Great Lakes could impact the distribution of rain vs snow in the Catskills which may affect future reservoir operations in the NYC Water Supply System

On the Frequency of Lake-Effect Snowfall in the Catskill Mountains

Meltwater from snow that falls in the Catskill/Delaware Watershed in the Catskill Mountains in south-central New York contributes to reservoirs that supply drinking water to approximately nine million people in and near New York City (NYC). Using the Interactive Multisensor Snow and Ice Mapping System (IMS) 4km snow maps from the National Oceanic and Atmospheric Administration's National Ice Center, we identified and tracked 28 lake-effect (LE) storms that deposited snow in the Catskill Mountains from 2004-2017. These storms, that generally originated from Lake Ontario, but sometimes from Lake Erie, represent an underestimate of the number of LE storms that contribute snowfall to the total Catskills snowpack because snowstorms are not visible on the IMS maps when they travel over already-snow-covered terrain. Using satellite, meteorological (including NEXRAD and National Weather Service Cooperative Observer Program), and reanalysis data we identify conditions that contributed to the LE snowstorms and map snow-cover extent (SCE) following the storms when possible. IMS 4km maps tend to overestimate SCE compared to MODerate-resolution Imaging Spectroradiometer (MODIS) and Landsat. Though the total amount of snow from each LE snow event that contributes snow to the Catskills is often small, there are a large number of events in some years that, together, add up to a great deal of snow. Changes that are predicted in LE snowfall events could impact the distribution of rain vs. snow in the Catskills which may affect future reservoir operations in the NYC Water Supply System and winter recreation in the Catskills

Remote Sensing of Snow Cover

Snow was easily identified in the first image obtained from the Television Infrared Operational Satellite-1 (TIROS-1) weather satellite in 1960 because the high albedo of snow presents a good contrast with most other natural surfaces. Subsequently, the National Oceanic and Atmospheric Administration (NOAA) began to map snow using satellite-borne instruments in 1966. Snow plays an important role in the Earth s energy balance, causing more solar radiation to be reflected back into space as compared to most snow-free surfaces. Seasonal snow cover also provides a critical water resource through meltwater emanating from rivers that originate from high-mountain areas such as the Tibetan Plateau. Meltwater from mountain snow packs flows to some of the world s most densely-populated areas such as Southeast Asia, benefiting over 1 billion people (Immerzeel et al., 2010). In this section, we provide a brief overview of the remote sensing of snow cover using visible and near-infrared (VNIR) and passive-microwave (PM) data. Snow can be mapped using the microwave part of the electromagnetic spectrum, even in darkness and through cloud cover, but at a coarser spatial resolution than when using VNIR data. Fusing VNIR and PM algorithms to produce a blended product offers synergistic benefits. Snow-water equivalent (SWE), snow extent, and melt onset are important parameters for climate models and for the initialization of atmospheric forecasts at daily and seasonal time scales. Snowmelt data are also needed as input to hydrological models to improve flood control and irrigation management

North American snow extent: 19001994

ABSTRACT Historical fluctuations of North American snow extent from November through March are reconstructed back to 1900 using a combination of satellite and station observations. Using results of principal components analyses (PCA) from a companion study (Frei, A. and Robinson, D.A. Int. J. Climatol., this volume), simple and multiple linear regression models are used to take advantage of the spatial coverage of satellite observations and the temporal extent of station observations. This analysis more than triples the remotely-sensed record length, which begins in 1972. Model results indicate that Nort

A Review of Global Satellite-Derived Snow Products

Snow cover over the Northern Hemisphere plays a crucial role in the Earth's hydrology and surface energy balance, and modulates feedbacks that control variations of global climate. While many of these variations are associated with exchanges of energy and mass between the land surface and the atmosphere, other expected changes are likely to propagate downstream and affect oceanic processes in coastal zones. For example, a large component of the freshwater flux into the Arctic Ocean comes from snow melt. The timing and magnitude of this flux affects biological and thermodynamic processes in the Arctic Ocean, and potentially across the globe through their impact on North Atlantic Deep Water formation. Several recent global remotely sensed products provide information at unprecedented temporal, spatial, and spectral resolutions. In this article we review the theoretical underpinnings and characteristics of three key products. We also demonstrate the seasonal and spatial patterns of agreement and disagreement amongst them, and discuss current and future directions in their application and development. Though there is general agreement amongst these products, there can be disagreement over certain geographic regions and under conditions of ephemeral, patchy and melting snow

Examination of change factor methodologies for climate change impact assessment

Citation: Anandhi, A., Frei, A., Pierson, D. C., Schneiderman, E. M., Zion, M. S., Lounsbury, D., and Matonse, A. H. ( 2011), Examination of change factor methodologies for climate change impact assessment, Water Resour. Res., 47, W03501, doi:10.1029/2010WR009104.A variety of methods are available to estimate values of meteorological variables at future times and at spatial scales that are appropriate for local climate change impact assessment. One commonly used method is Change Factor Methodology (CFM), sometimes referred to as delta change factor methodology. Although more sophisticated methods exist, CFM is still widely applicable and used in impact analysis studies. While there are a number of different ways by which change factors (CFs) can be calculated and used to estimate future climate scenarios, there are no clear guidelines available in the literature to decide which methodologies are most suitable for different applications. In this study several categories of CFM (additive versus multiplicative and single versus multiple) for a number of climate variables are compared and contrasted. The study employs several theoretical case studies, as well as a real example from Cannonsville watershed, which supplies water to New York City, USA. Results show that in cases when the frequency distribution of Global Climate Model (GCM) baseline climate is close to the frequency distribution of observed climate, or when the frequency distribution of GCM future climate is close to the frequency distribution of GCM baseline climate, additive and multiplicative single CFMs provide comparable results. Two options to guide the choice of CFM are suggested. The first option is a detailed methodological analysis for choosing the most appropriate CFM. The second option is a default method for use under circumstances in which a detailed methodological analysis is too cumbersome

A high quality Arabidopsis transcriptome for accurate transcript-level analysis of alternative splicing

Alternative splicing generates multiple transcript and protein isoforms from the same gene and thus is important in gene expression regulation. To date, RNA-sequencing (RNA-seq) is the standard method for quantifying changes in alternative splicing on a genome-wide scale. Understanding the current limitations of RNA-seq is crucial for reliable analysis and the lack of high quality, comprehensive transcriptomes for most species, including model organisms such as Arabidopsis, is a major constraint in accurate quantification of transcript isoforms. To address this, we designed a novel pipeline with stringent filters and assembled a comprehensive Reference Transcript Dataset for Arabidopsis (AtRTD2) containing 82,190 non-redundant transcripts from 34 212 genes. Extensive experimental validation showed that AtRTD2 and its modified version, AtRTD2-QUASI, for use in Quantification of Alternatively Spliced Isoforms, outperform other available transcriptomes in RNA-seq analysis. This strategy can be implemented in other species to build a pipeline for transcript-level expression and alternative splicing analyses

In search of the authentic nation: landscape and national identity in Canada and Switzerland

While the study of nationalism and national identity has flourished in the last decade, little attention has been devoted to the conditions under which natural environments acquire significance in definitions of nationhood. This article examines the identity-forming role of landscape depictions in two polyethnic nation-states: Canada and Switzerland. Two types of geographical national identity are identified. The first – what we call the ‘nationalisation of nature’– portrays zarticular landscapes as expressions of national authenticity. The second pattern – what we refer to as the ‘naturalisation of the nation’– rests upon a notion of geographical determinism that depicts specific landscapes as forces capable of determining national identity. The authors offer two reasons why the second pattern came to prevail in the cases under consideration: (1) the affinity between wild landscape and the Romantic ideal of pure, rugged nature, and (2) a divergence between the nationalist ideal of ethnic homogeneity and the polyethnic composition of the two societies under consideration