Radiative Climatology of the North Slope of Alaska and the Adjacent Arctic Ocean

Similar documents
A 10 year climatology of Arctic cloud fraction and radiative forcing at Barrow, Alaska

An Annual Cycle of Arctic Cloud Microphysics

Antarctic Cloud Radiative Forcing at the Surface Estimated from the AVHRR Polar Pathfinder and ISCCP D1 Datasets,

P1.34 MULTISEASONALVALIDATION OF GOES-BASED INSOLATION ESTIMATES. Jason A. Otkin*, Martha C. Anderson*, and John R. Mecikalski #

Changes in seasonal cloud cover over the Arctic seas from satellite and surface observations

PUBLICATIONS. Journal of Geophysical Research: Atmospheres

Outline: 1) Extremes were triggered by anomalous synoptic patterns 2) Cloud-Radiation-PWV positive feedback on 2007 low SIE

Microphysical Properties of Single and Mixed-Phase Arctic Clouds Derived From Ground-Based AERI Observations

The Northern Hemisphere Sea ice Trends: Regional Features and the Late 1990s Change. Renguang Wu

Observational Needs for Polar Atmospheric Science

Interannual Variations of Arctic Cloud Types:

UV RADIATION IN THE SOUTHERN SEAS IN SUMMER 2000 Gerd Wendler and Brian Hartmann Geophysical Institute, University of Alaska, Fairbanks, Alaska 99775

VALIDATION OF THE OSI SAF RADIATIVE FLUXES

Observations of Integrated Water Vapor and Cloud Liquid Water at SHEBA. James Liljegren

A Longwave Broadband QME Based on ARM Pyrgeometer and AERI Measurements

History of Earth Radiation Budget Measurements With results from a recent assessment

THE LAND-SAF SURFACE ALBEDO AND DOWNWELLING SHORTWAVE RADIATION FLUX PRODUCTS

Coupling Climate to Clouds, Precipitation and Snow

OPTIMISING THE TEMPORAL AVERAGING PERIOD OF POINT SURFACE SOLAR RESOURCE MEASUREMENTS FOR CORRELATION WITH AREAL SATELLITE ESTIMATES

Seasonal and interannual variations of top-of-atmosphere irradiance and cloud cover over polar regions derived from the CERES data set

Clouds, Haze, and Climate Change

AT350 EXAM #1 September 23, 2003

Northern New England Climate: Past, Present, and Future. Basic Concepts

APPLICATIONS WITH METEOROLOGICAL SATELLITES. W. Paul Menzel. Office of Research and Applications NOAA/NESDIS University of Wisconsin Madison, WI

13.10 RECENT ARCTIC CLIMATE TRENDS OBSERVED FROM SPACE AND THE CLOUD-RADIATION FEEDBACK

1. The frequency of an electromagnetic wave is proportional to its wavelength. a. directly *b. inversely

Surface Radiation Budget from ARM Satellite Retrievals

EVALUATING SOLAR RESOURCE VARIABILITY FROM SATELLITE AND GROUND-BASED OBSERVATIONS

ATMS 321 Problem Set 1 30 March 2012 due Friday 6 April. 1. Using the radii of Earth and Sun, calculate the ratio of Sun s volume to Earth s volume.

Annex I to Target Area Assessments

All objects emit radiation. Radiation Energy that travels in the form of waves Waves release energy when absorbed by an object. Earth s energy budget

- global radiative energy balance

Understanding the Greenhouse Effect

Journal of the Meteorological Society of Japan, Vol. 75, No. 1, pp , Day-to-Night Cloudiness Change of Cloud Types Inferred from

Seasonal Variations of the Urban Heat Island Effect:

The Atmosphere. Importance of our. 4 Layers of the Atmosphere. Introduction to atmosphere, weather, and climate. What makes up the atmosphere?

CLIMATE CHANGE Albedo Forcing ALBEDO FORCING

Arctic Climate Change. Glen Lesins Department of Physics and Atmospheric Science Dalhousie University Create Summer School, Alliston, July 2013

Monitoring Climate Change from Space

Variability in Global Top-of-Atmosphere Shortwave Radiation Between 2000 And 2005

Radiation Quantities in the ECMWF model and MARS

Assessing the Radiative Impact of Clouds of Low Optical Depth

Extreme Weather and Climate Change: the big picture Alan K. Betts Atmospheric Research Pittsford, VT NESC, Saratoga, NY

Lecture 3. Background materials. Planetary radiative equilibrium TOA outgoing radiation = TOA incoming radiation Figure 3.1

Land Surface Temperature Measurements From the Split Window Channels of the NOAA 7 Advanced Very High Resolution Radiometer John C.

1.0 BACKGROUND 1.1 Surface Radiation

Benchmarking Polar WRF in the Antarctic *

Electromagnetic Radiation. Radiation and the Planetary Energy Balance. Electromagnetic Spectrum of the Sun

Insolation and Temperature variation. The Sun & Insolation. The Sun (cont.) The Sun

Cloud Cover over the South Pole from Visual Observations, Satellite Retrievals, and Surface-Based Infrared Radiation Measurements

Radiation Fluxes During ZCAREX-99: Measurements and Calculations

Extratropical and Polar Cloud Systems

Analysis of Cloud-Radiation Interactions Using ARM Observations and a Single-Column Model

The Climatology of Clouds using surface observations. S.G. Warren and C.J. Hahn Encyclopedia of Atmospheric Sciences.

Chapter 2 Available Solar Radiation

Radiation balance of the Earth. 6. Earth radiation balance under present day conditions. Top of Atmosphere (TOA) Radiation balance

Reconciling different observational data sets from Surface Heat Budget of the Arctic Ocean (SHEBA) for model validation purposes

Lake parameters climatology for cold start runs (lake initialization) in the ECMWF forecast system

Modeling Challenges At High Latitudes. Judith Curry Georgia Institute of Technology

HEATING THE ATMOSPHERE

Temporal Variability of the Energy Balance of Thick Arctic Pack Ice

1. GLACIER METEOROLOGY - ENERGY BALANCE

Changes in Earth s Albedo Measured by satellite

Solar Insolation and Earth Radiation Budget Measurements

BEAUFORT SEA ICE CONCENTRATION AND THE CLIMATE OF THE ALASKAN NORTH SLOPE

Experimental and Theoretical Studies of Ice-Albedo Feedback Processes in the Arctic Basin

Development and Validation of Polar WRF

Chapter 2 Solar and Infrared Radiation

Arctic climate projections and progress towards a new CCSM. Marika Holland NCAR

TRENDS IN DIRECT NORMAL SOLAR IRRADIANCE IN OREGON FROM

Interannual variability of top-ofatmosphere. CERES instruments

Which Climate Model is Best?

Bugs in JRA-55 snow depth analysis

(1) AEMET (Spanish State Meteorological Agency), Demóstenes 4, Málaga, Spain ABSTRACT

Lecture 3: Global Energy Cycle

New Insights into Aerosol Asymmetry Parameter

Regional Outlook for the Bering-Chukchi-Beaufort Seas Contribution to the 2018 Sea Ice Outlook

Arctic Atmospheric Rivers: Linking Atmospheric Synoptic Transport, Cloud Phase, Surface Energy Fluxes and Sea-Ice Growth

A FIRST INVESTIGATION OF TEMPORAL ALBEDO DEVELOPMENT OVER A MAIZE PLOT

Radiative Effects of Contrails and Contrail Cirrus

J2.11 PROPERTIES OF WATER-ONLY, MIXED-PHASE, AND ICE-ONLY CLOUDS OVER THE SOUTH POLE: PRELIMINARY RESULTS

Observed Southern Ocean Cloud Properties and Shortwave Reflection

Remote sensing of sea ice

Modeling the Arctic Climate System

C) wavelength C) eastern horizon B) the angle of insolation is high B) increases, only D) thermosphere D) receive low-angle insolation

Satellite-based estimate of global aerosol-cloud radiative forcing by marine warm clouds

M. Mielke et al. C5816

Spectral Albedos. a: dry snow. b: wet new snow. c: melting old snow. a: cold MY ice. b: melting MY ice. d: frozen pond. c: melting FY white ice

Comparison of Convection Characteristics at the Tropical Western Pacific Darwin Site Between Observation and Global Climate Models Simulations

Evaluation of a New Land Surface Model for JMA-GSM

ON THE SHORTWAVE RADIATION PARAMETERIZATION IN THERMODYNAMIC SEA ICE MODELS IN THE BALTIC SEA

Lecture 9: Climate Sensitivity and Feedback Mechanisms

Climate Feedbacks from ERBE Data

Influence of changes in sea ice concentration and cloud cover on recent Arctic surface temperature trends

Global Climate Change

Page 1. Name:

( 1 d 2 ) (Inverse Square law);

Name Per Date Earth Science Climate & Insolation Test

Which graph best shows the relationship between intensity of insolation and position on the Earth's surface? A) B) C) D)

ATMOS 5140 Lecture 1 Chapter 1

Transcription:

Radiative Climatology of the North Slope of Alaska and the Adjacent Arctic Ocean C. Marty, R. Storvold, and X. Xiong Geophysical Institute University of Alaska Fairbanks, Alaska K. H. Stamnes Stevens Institute of Technology Hoboken, New Jersey B. D. Zak Sandia National Laboratories Albuquerque, New Mexico Introduction Recent climate modeling results point to the Arctic as a region that is particularly sensitive to global climate change (e.g., IPCC 1997). The North Slope of Alaska-Adjacent Arctic Ocean (NSA-AAO) Cloud and Radiation Testbed (CART) sites of the Atmospheric Radiation Measurement (ARM) Program are designed to collect data on temperature-ice-albedo and water vapor-cloud-radiation feedbacks are believed to be important to the predicted global warming (Stamnes et al. 1999). The main goals of the project are improving radiative transfer models in the Arctic environment and the testing of satellite remote sensing algorithms. At the two NSA-AAO ARM sites, radiation data has now been collected through more than a complete annual cycle. Barrow is the main NSA-AAO site and represents the Arctic Ocean coastal climate whereas Atqasuk (100 km inland) on the other side is anticipated to have more continental character. What we present here is a preliminary investigation on one year (2000) of data of radiative fluxes and standard meteorological elements of these two sites and compare it with similar results obtained in the Arctic Ocean during the one-year (1997/98) Surface Heat Budget in the Arctic (SHEBA) Experiment. The radiative energy balance is calculated from upward and downward looking broadband radiometers. Albedo derived from broadband measurements is used to verify satellites derived albedo, which plays a key role for the determination of the radiation budget from space. Furthermore, we show the implementation and verification of a Clear-Sky Index (CSI), which can be used to distinguish between clear and cloudy sky at remote sites where we would otherwise not be able to do so. 1

Radiation Fluxes Shortwave (SW) and longwave (LW) broadband radiation fluxes on all three sites were measured with an Eppley Precision Spectral Pyranometer (PSP), respectively an Eppley Precision Infrared Radiometer (PIR). All instruments were ventilated with slightly preheated air to prevent frost on the domes. The PIRs were operated shaded on a solar tracker because the dome is not absolutely blocking the direct sun from the detector and because direct solar radiation causes a non-uniform solar heating of the PIR dome. The radiation fluxes are stored as 1-minute averages, which we used to derive daily mean values. Finally, to better show the seasonal cycle the daily mean values were smoothed by a 30-day moving average. The available energy from the radiation budget is, at all three sites, strongly dominated by the albedo. Net radiation in Barrow shows positive values from the beginning of April to the end of September with a maximum of about 200 W m -2 at the end of June and the beginning of July (Figure 1). Values above 50 W m -2 can only be observed from the beginning of June to mid-september, i.e., according to the albedo from the beginning of the snowmelt to the beginning of the next permanent winter snow cover. Minimum values of net radiation (about -80 W m -2 ) are observed during December and January when no SW radiation is available since the sun is below the horizon. Net LW radiation varies shows no seasonal cycle and varies normally between almost zero and -70 W m -2. Few daily mean values between mid-january and April even show positive values of net LW radiation (up to about 30 W m -2 ) due to a strong inversion (despite the everlasting wind) near the ground. Longwave downwelling radiation can vary between about 120 W m -2 in winter and almost 400 W m -2 in summer. The daily mean values of direct solar radiation indicate that most clear-sky days occurred from March until mid-april with a few exceptions in July, August, and September. The clear decrease of global radiation (maximum values almost 350 W m -2 ) in the second half of the summer is caused by the dominating stratoform cloud cover during that time of the year. The downward looking instruments in Atqasuk were unfortunately not available before June. Hence, no net fluxes could be calculated before that time. The available data show much higher net radiation during early summer (maximum 300 W m -2 ) in Atqasuk than in Barrow (Figure 2). This is mainly caused by about 50 W m -2 more daily global radiation (maximum 450 W m -2 ), which is even enhanced by a slightly lower albedo in Atqasuk than in Barrow. The higher direct solar radiation in Atqasuk indicates that the higher global radiation is caused by less (or thinner) summer cloud cover in Atqasuk than in Barrow. This is confirmed by the comparison of the temperature normalized LW downwelling radiation (Figure 3) of the two sites. The LW downwelling radiation itself is very similar at the two sites despite the less cloud cover in Atqasuk because the mean temperature (Figure 4) in summer is quite higher in Atqasuk than in Barrow. The absolute humidity (Figure 5) is too low at both sites to cause a significant difference in the atmospheric radiation. The normalized LW downwelling radiation can therefore be used as an indicator for cloud cover at these two sites. The winter comparison of the normalized LW downwelling radiation indicates more cloud cover situations in Atqasuk than in Barrow and vice versa in summer. These results could be confirmed by a study, which used light detection and ranging (LIDAR) measurements in Atqasuk and Barrow to derive cloud cover at the two stations (Storvold et al. 2001). In winter (in absence of the sun) the larger number of clear-sky situations is 2

Figure 1. Annual cycle of the different radiation fluxes at Barrow during the year 2000. 3

Figure 2. Annual cycle of the different radiation fluxes at Atqasuk during the year 2000. 4

Figure 3. Temperature normalized LW downwelling radiation in Barrow and Atqasuk during the year 2000. Figure 4. Air temperature in Barrow and Atqasuk during the year 2000. 5

Figure 5. Water vapor (WV) pressure in Barrow and Atqasuk during the year 2000. responsible for the lower air temperatures in Atqasuk than in Barrow. The warmer summer temperatures in Atqasuk cause an earlier snowmelt (about beginning of June), which according to the albedo values is about ten days earlier than in Barrow. The SHEBA site was operational from October 1997 to September 1998 on a multi-year ice floe in the Arctic Ocean about 800 km north of Barrow. Despite the time and local differences of SHEBA to the two others sites some similarities and differences are worth to be compared. The seasonal cycle of net radiation (Figure 6) is not as pronounced due to the small change in the sea-ice albedo from winter (0.8) to summer (0.6). In contrast to Barrow, daily mean values of LW net radiation at the SHEBA site hardly got positive. Longwave downwelling radiation shows similar minimum values (about 120 W m -2 ) in winter, whereas the maximum values in summer only reach a little bit more than 300 W m -2. The smaller direct radiation values indicate that the high global radiation is mainly caused by multiple reflection between the sea-ice and low-level clouds. Verification of Satellite Derived Albedo Surface albedo is one of the most important factors influencing the radiation budget of the earthatmosphere system. The Arctic surface albedo is characterized by a rapid and significant change of surface physical conditions during the short melt season. NSA-AAO data from Barrow was used to compare satellite-derived albedo during spring and summer 2000. 6

Figure 6. Annual cycle of the different radiation fluxes at SHEBA during the year 2000. 7

Advanced Very High Resolution Radiometer (AVHRR) data from the National Oceanic and Atmospheric Administration (NOAA) polar orbiting satellites were used to retrieve broadband albedo from space using channel 1 (visible) and channel 2 (near infrared) and applying narrow-to-broadband conversion (Xiong and Stamnes 2001). To improve accuracy only clear-sky near overhead passes with solar zenith angle < 70 were used. The following comparison (Figure 7) between the satellite-derived albedo and the measured surface albedo (derived using daily mean up- and downwelling values) show encouraging good results for spring and first half of summer. Figure 7. Measured and satellite-retrieved surface albedo during the year 1999 in Barrow. The 10 percent lower satellite-derived albedo in spring and during the melt period can be explained with the large AVHRR grid size, which also includes icy ponds and windblown ridges. Errors in the AVHRR albedo seem to increase in the second part of the summer. This might be due to the fact that an almost permanent stratoform cloud layer during this time prevents the measurement of the necessary number of clear-sky pixels. Detection of Clear-Sky Situations Detailed climatological analysis and many investigations on radiation data demand for the distinction between clear-sky and cloudy sky situations. Approaches used so far, are based on synoptic sky 8

observations or SW measurements. The first includes temporal miss-matches and subjectivity. The second is limited to daytime hours. Furthermore, these two as well as other methods need special instrumentation or observations. Our approach (Marty and Philipona 2000) uses LW downwelling radiation LW d and the standard meteorological elements, air temperature T a and humidity (water vapor pressure) e a. The method is based on the idea to continuously compare the measured apparent emissivity ε A with the calculated theoretical clear-sky apparent emissivity ε AC at the same moment. Whereas ε A = LW d / σ T a 4 ε AC is calculated with an empirical formula, which uses measured T a and e a. A CSI can thus be defined: CSI = ε A / ε AC, CSI 1 clear-sky, CSI > cloud sky or overcast Figure 8 shows hourly values of CSI- and LIDAR-detected clouds during March 2000 at the ARM site at Barrow. Since the LIDAR is looking only at a small fraction of the sky straight above the instrument, the neighboring hourly values were included in the determination between clear and cloudy sky. The intercomparison generally shows good agreement between CSI and LIDAR. Some uncertainties might be explained with temporal and field-of-view differences between the two methods. Figure 8. Intercomparison between the CSI and LIDAR measurements during March 2000 in Barrow. 9

Conclusions Although Atqasuk is only about 100 km inland of Barrow and no topography is in between the two sites, the presented results demonstrate that Atqasuk experiences a somewhat more continental climate than Barrow, at least during the first year (2000) of measurements. Hence, Atqasuk shows a colder winter, but a warmer summer. An investigation of the temperature normalized LW downwelling radiation indicates that the different temperature regime might partly be driven by the seasonally different cloud cover in Atqasuk and Barrow. The higher number of spring cloudy sky situation would also explain the measured earlier snowmelt (and hence the earlier decrease in albedo) in Atqasuk compared with Barrow. The satellite-derived albedo revealed on the one hand that stations like Barrow, Atqasuk, or SHEBA are a necessary condition if we want to improve our ability to derive radiation fluxes from space. Otherwise limitations due to a lack of clear-sky during summer in this part of the planet were also shown but should be significantly reduced with the new generation of space borne instruments. The CSI algorithm applied to the Barrow data demonstrated that it is possible to continuously detect clear-sky situations with the help of LW atmospheric radiation and standard meteorological elements. The independency from solar radiation measurements makes this method very suitable for clear-sky detection during Arctic winter. Acknowledgements Data gaps in Barrow could partially be filled with data from the nearby NOAA Climate Monitoring and Diagnostics Laboratory station. San Diego State University kindly provided us with meteorological data of their field experiment in Atqasuk, what allowed us to fill some of our data gaps in Atqasuk. Corresponding Author C. Marty, chris@gi.alaska.edu, (907) 474-7360 References IPCC Special Report (R. T. Watson, M. C. Zinyowera, and R. H. Moss), 1997: The regional impacts of climate change: An assessment of vulnerability, a special report of IPCC working group II, Cambridge University Press, United Kingdom. Marty, C., and R. Philipona, 2000: The Clear-Sky Index to separate clear-sky from cloudy sky situations in climate research. GRL, 27(17), 2649-2652. Stamnes K., R. G. Ellingson, J. A. Curry, J. E. Walsh, and B. D. Zak, 1999: Review of science issues, deployment strategy, and status for the ARM North Slope of Alaska-Adjacent Arctic Ocean Climate Research site. J. of Climate, 12, 46-63. 10

Storvold R., Ch. Marty, K. Stamnes, and B. D. Zak, 2001: Seasonal variability in cloud cover, cloud base height, and cloud liquid water content at the North Slope of Alaska and the Adjacent Arctic Ocean. This proceedings. Xiong X., and K. Stamnes, 2001: Surface albedo over high Arctic Ocean derived from AVHRR and its validation with SHEBA data. J. Appl. Meteorology, submitted. 11