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Anthony J. Baran, Peter Hill, David Walters, Steven C. Hardiman, Kalli Furtado, Paul R. Field, and James Manners

Abstract

The impact of two different coupled cirrus microphysics–radiation parameterizations on the zonally averaged temperature and humidity biases in the tropical tropopause layer (TTL) of a Met Office climate model configuration is assessed. One parameterization is based on a linear coupling between a model prognostic variable, the ice mass mixing ratio q i, and the integral optical properties. The second is based on the integral optical properties being parameterized as functions of q i and temperature, T c, where the mass coefficients (i.e., scattering and extinction) are parameterized as nonlinear functions of the ratio between q i and T c. The cirrus microphysics parameterization is based on a moment estimation parameterization of the particle size distribution (PSD), which relates the mass moment (i.e., second moment if mass is proportional to size raised to the power of 2) of the PSD to all other PSD moments through the magnitude of the second moment and T c. This same microphysics PSD parameterization is applied to calculate the integral optical properties used in both radiation parameterizations and, thus, ensures PSD and mass consistency between the cirrus microphysics and radiation schemes. In this paper, the temperature-non-dependent and temperature-dependent parameterizations are shown to increase and decrease the zonally averaged temperature biases in the TTL by about 1 K, respectively. The temperature-dependent radiation parameterization is further demonstrated to have a positive impact on the specific humidity biases in the TTL, as well as decreasing the shortwave and longwave biases in the cloudy radiative effect. The temperature-dependent radiation parameterization is shown to be more consistent with TTL and global radiation observations.

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Ross N. Hoffman, Peter Dailey, Susanna Hopsch, Rui M. Ponte, Katherine Quinn, Emma M. Hill, and Brian Zachry

Abstract

Sea level is rising as the World Ocean warms and ice caps and glaciers melt. Published estimates based on data from satellite altimeters, beginning in late 1992, suggest that the global mean sea level has been rising on the order of 3 mm yr−1. Local processes, including ocean currents and land motions due to a variety of causes, modulate the global signal spatially and temporally. These local signals can be much larger than the global signal, and especially so on annual or shorter time scales.

Even increases on the order of 10 cm in sea level can amplify the already devastating losses that occur when a hurricane-driven storm surge coincides with an astronomical high tide. To quantify the sensitivity of property risk to increasing sea level, changes in expected annual losses to property along the U.S. Gulf and East Coasts are calculated as follows. First, observed trends in sea level rise from tide gauges are extrapolated to the year 2030, and these changes are interpolated to all coastal locations. Then a 10 000-yr catalog of simulated hurricanes is used to define critical wind parameters for each event. These wind parameters then drive a parametric time-evolving storm surge model that accounts for bathymetry, coastal geometry, surface roughness, and the phase of the astronomical tide. The impact of the maximum storm surge height on a comprehensive inventory of commercial and residential property is then calculated, using engineering models that take into account the characteristics of the full range of construction types.

Average annual losses projected to the year 2030 are presented for regions and key states and are normalized by aggregate property value on a zip code by zip code basis. Comparisons to the results of a control run reflecting the risk today quantify the change in risk per dollar of property on a percentage basis. Increases in expected losses due to the effect of sea level rise alone vary by region, with increases of 20% or more being common. Further sensitivity tests quantify the impact on the risk of sea level rise plus additional factors, such as changes in hurricane frequency and intensity as a result of rising sea surface temperatures.

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Jake J. Gristey, J. Christine Chiu, Robert J. Gurney, Keith P. Shine, Stephan Havemann, Jean-Claude Thelen, and Peter G. Hill

Abstract

The spectrum of reflected solar radiation emerging at the top of the atmosphere is rich with Earth system information. To identify spectral signatures in the reflected solar radiation and directly relate them to the underlying physical properties controlling their structure, over 90 000 solar reflectance spectra are computed over West Africa in 2010 using a fast radiation code employing the spectral characteristics of the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY). Cluster analysis applied to the computed spectra reveals spectral signatures related to distinct surface properties, and cloud regimes distinguished by their spectral shortwave cloud radiative effect (SWCRE). The cloud regimes exhibit a diverse variety of mean broadband SWCREs, and offer an alternative approach to define cloud type for SWCRE applications that does not require any prior assumptions. The direct link between spectral signatures and distinct physical properties extracted from clustering remains robust between spatial scales of 1, 20, and 240 km, and presents an excellent opportunity to understand the underlying properties controlling real spectral reflectance observations. Observed SCIAMACHY spectra are assigned to the calculated spectral clusters, showing that cloud regimes are most frequent during the active West African monsoon season of June–October in 2010, and all cloud regimes have a higher frequency of occurrence during the active monsoon season of 2003 compared with the inactive monsoon season of 2004. Overall, the distinct underlying physical properties controlling spectral signatures show great promise for monitoring evolution of the Earth system directly from solar spectral reflectance observations.

Open access
Carlo Cafaro, Beth J. Woodhams, Thorwald H. M. Stein, Cathryn E. Birch, Stuart Webster, Caroline L. Bain, Andrew Hartley, Samantha Clarke, Samantha Ferrett, and Peter Hill

Abstract

Convection-permitting ensemble prediction systems (CP-ENS) have been implemented in the midlatitudes for weather forecasting time scales over the past decade, enabled by the increase in computational resources. Recently, efforts are being made to study the benefits of CP-ENS for tropical regions. This study examines CP-ENS forecasts produced by the Met Office over tropical East Africa, for 24 cases in the period April–May 2019. The CP-ENS, an ensemble with parameterized convection (Glob-ENS), and their deterministic counterparts are evaluated against rainfall estimates derived from satellite observations (GPM-IMERG). The CP configurations have the best representation of the diurnal cycle, although heavy rainfall amounts are overestimated compared to observations. Pairwise comparisons between the different configurations reveal that the CP-ENS is generally the most skillful forecast for both 3- and 24-h accumulations of heavy rainfall (97th percentile), followed by the CP deterministic forecast. More precisely, probabilistic forecasts of heavy rainfall, verified using a neighborhood approach, show that the CP-ENS is skillful at scales greater than 100 km, significantly better than the Glob-ENS, although not as good as found in the midlatitudes. Skill decreases with lead time and varies diurnally, especially for CP forecasts. The CP-ENS is underspread both in terms of forecasting the locations of heavy rainfall and in terms of domain-averaged rainfall. This study demonstrates potential benefits in using CP-ENS for operational forecasting of heavy rainfall over tropical Africa and gives specific suggestions for further research and development, including probabilistic forecast guidance.

Open access
Peter A. Bieniek, Uma S. Bhatt, Richard L. Thoman, Heather Angeloff, James Partain, John Papineau, Frederick Fritsch, Eric Holloway, John E. Walsh, Christopher Daly, Martha Shulski, Gary Hufford, David F. Hill, Stavros Calos, and Rudiger Gens

Abstract

Alaska encompasses several climate types because of its vast size, high-latitude location, proximity to oceans, and complex topography. There is a great need to understand how climate varies regionally for climatic research and forecasting applications. Although climate-type zones have been established for Alaska on the basis of seasonal climatological mean behavior, there has been little attempt to construct climate divisions that identify regions with consistently homogeneous climatic variability. In this study, cluster analysis was applied to monthly-average temperature data from 1977 to 2010 at a robust set of weather stations to develop climate divisions for the state. Mean-adjusted Advanced Very High Resolution Radiometer surface temperature estimates were employed to fill in missing temperature data when possible. Thirteen climate divisions were identified on the basis of the cluster analysis and were subsequently refined using local expert knowledge. Divisional boundary lines were drawn that encompass the grouped stations by following major surrounding topographic boundaries. Correlation analysis between station and gridded downscaled temperature and precipitation data supported the division placement and boundaries. The new divisions north of the Alaska Range were the North Slope, West Coast, Central Interior, Northeast Interior, and Northwest Interior. Divisions south of the Alaska Range were Cook Inlet, Bristol Bay, Aleutians, Northeast Gulf, Northwest Gulf, North Panhandle, Central Panhandle, and South Panhandle. Correlations with various Pacific Ocean and Arctic climatic teleconnection indices showed numerous significant relationships between seasonal division average temperature and the Arctic Oscillation, Pacific–North American pattern, North Pacific index, and Pacific decadal oscillation.

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Ian M. Brooks, Margaret J. Yelland, Robert C. Upstill-Goddard, Philip D. Nightingale, Steve Archer, Eric d'Asaro, Rachael Beale, Cory Beatty, Byron Blomquist, A. Anthony Bloom, Barbara J. Brooks, John Cluderay, David Coles, John Dacey, Michael Degrandpre, Jo Dixon, William M. Drennan, Joseph Gabriele, Laura Goldson, Nick Hardman-Mountford, Martin K. Hill, Matt Horn, Ping-Chang Hsueh, Barry Huebert, Gerrit De Leeuw, Timothy G. Leighton, Malcolm Liddicoat, Justin J. N. Lingard, Craig Mcneil, James B. Mcquaid, Ben I. Moat, Gerald Moore, Craig Neill, Sarah J. Norris, Simon O'Doherty, Robin W. Pascal, John Prytherch, Mike Rebozo, Erik Sahlee, Matt Salter, Ute Schuster, Ingunn Skjelvan, Hans Slagter, Michael H. Smith, Paul D. Smith, Meric Srokosz, John A. Stephens, Peter K. Taylor, Maciej Telszewski, Roisin Walsh, Brian Ward, David K. Woolf, Dickon Young, and Henk Zemmelink

Abstract

No Abstract available.

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Ian M. Brooks, Margaret J. Yelland, Robert C. Upstill-Goddard, Philip D. Nightingale, Steve Archer, Eric d'Asaro, Rachael Beale, Cory Beatty, Byron Blomquist, A. Anthony Bloom, Barbara J. Brooks, John Cluderay, David Coles, John Dacey, Michael DeGrandpre, Jo Dixon, William M. Drennan, Joseph Gabriele, Laura Goldson, Nick Hardman-Mountford, Martin K. Hill, Matt Horn, Ping-Chang Hsueh, Barry Huebert, Gerrit de Leeuw, Timothy G. Leighton, Malcolm Liddicoat, Justin J. N. Lingard, Craig McNeil, James B. McQuaid, Ben I. Moat, Gerald Moore, Craig Neill, Sarah J. Norris, Simon O'Doherty, Robin W. Pascal, John Prytherch, Mike Rebozo, Erik Sahlee, Matt Salter, Ute Schuster, Ingunn Skjelvan, Hans Slagter, Michael H. Smith, Paul D. Smith, Meric Srokosz, John A. Stephens, Peter K. Taylor, Maciej Telszewski, Roisin Walsh, Brian Ward, David K. Woolf, Dickon Young, and Henk Zemmelink

As part of the U.K. contribution to the international Surface Ocean-Lower Atmosphere Study, a series of three related projects—DOGEE, SEASAW, and HiWASE—undertook experimental studies of the processes controlling the physical exchange of gases and sea spray aerosol at the sea surface. The studies share a common goal: to reduce the high degree of uncertainty in current parameterization schemes. The wide variety of measurements made during the studies, which incorporated tracer and surfactant release experiments, included direct eddy correlation fluxes, detailed wave spectra, wind history, photographic retrievals of whitecap fraction, aerosolsize spectra and composition, surfactant concentration, and bubble populations in the ocean mixed layer. Measurements were made during three cruises in the northeast Atlantic on the RRS Discovery during 2006 and 2007; a fourth campaign has been making continuous measurements on the Norwegian weather ship Polarfront since September 2006. This paper provides an overview of the three projects and some of the highlights of the measurement campaigns.

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