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The Mount Washington Observatory Regional Mesonet (MWRM) is a network of 18 remote meteorological monitoring stations (as of 2022), including the Auto Road Vertical Profile (ARVP), located across the White Mountains of northern New Hampshire. Each station measures temperature and relative humidity, with additional variables at many locations. All stations need to withstand the frequent combination of intense cold, high precipitation amounts, icing, and hurricane-force winds in a mountain environment. Due to these challenges, the MWRM employs rugged instrumentation, an innovative radio-communications relay approach, and carefully selected sites that balance ideal measuring environments with station survivability. Data collected from the MWRM are used operationally by forecasters (including Mount Washington Observatory and National Weather Service staff) to validate model guidance, by alpine and climate scientists, by recreationalists accessing conditions in the backcountry, by groups operating on the mountain (Cog Railway, toll Auto Road), and by search and rescue organizations. This paper provides a detailed description of the network, with emphasis on how the challenging climate and terrain of this mountain region impacts sensor selection, site maintenance, and overall operation. Significance Statement: The mountain environment is a heterogeneous landscape, and interactions between the atmosphere and terrain can cause a wide variety of conditions across time and space. Our network of remote stations at different elevations across the White Mountains allows data users to understand how the weather varies spatially across the mountain range where conditions on higher peaks can be drastically, and dangerously, different. Sharing information about the MWRM can help other groups establish networks in similar challenging environments, and broaden our understanding of weather and climate in mountainous regions. [ABSTRACT FROM AUTHOR]

This paper describes the Comprehensive Pacific Rainfall Database (PACRAIN), which contains daily and monthly precipitation records from the tropical Pacific basin. The database is a collection of observations from a variety of sources, including one, the Schools of the Pacific Rainfall Climate Experiment (SPaRCE), that is unique to PACRAIN. SPaRCE is a cooperative field project and involves schools from various Pacific island and atoll nations. Recent enhancements to the database, including improved quality control, observation and data entry standardization, expansion of the network, increased collaboration with local meteorological directors, and enhanced high-resolution data (e.g., on hourly or minute time scales), are discussed. This paper also outlines some of the internal data and Web-based access specifics of the database. To illustrate the potential usefulness of the data, two examples of research using the PACRAIN database are provided and discussed. The first is an analysis of temporal changes in the extreme event characteristics of daily precipitation across the region. The second is an illustration of how the PACRAIN database can be used to analyze satellite-based precipitation algorithms. [ABSTRACT FROM AUTHOR]

First-year ice has replaced multiyear ice in the Northern Sea Route area since 2008. In this area, sea ice survival during summer substantially depends on first-year ice thickness at melt onset, and thus monitoring of first-year ice thickness in the freezing period is a key to forecasting sea ice distributions in the following summer. In this paper we introduce a new algorithm to estimate flat first-year ice draft using brightness temperature data measured by the Advanced Microwave Scanning Radiometer-2 (AMSR2). The algorithm uses a gradient ratio (GR) of 18- and 36-GHz vertically polarized brightness temperatures based on decreases in sea ice emissivity in higher AMSR2 frequency channels with thermodynamic growth associated with an increase in volume scattering. Such spectral characteristics of the emissivity are examined by comparing GR values with flat first-year ice draft extracted by mode values of in situ draft data measured by a moored ice profiling sonar. The accuracy of the daily draft estimated from GR values after applying proper noise filters is about 10 cm for a draft range of 0.4–1.2 m. [ABSTRACT FROM AUTHOR]

The Nebraska Mesonet was established in 1981 as one of the nation's first automated state weather networks. "Automated" is defined by the nature of the observations being made and recorded by machine, as opposed to observations made and recorded manually. At the time of inception, the five observing locations were geared toward servicing agricultural production applications. The Nebraska Mesonet has grown to 69 stations (as of 2018) and is now a multipurpose environmental observing network under the Nebraska State Climate Office (NSCO). The network is composed of environmental observation stations, sited using best practices for mesoscale and microscale environment situations. Precise observations are acquired using high-quality instrumentation, following manufacturer recommendations for calibrations and maintenance. Calibrations are performed in the NSCO calibration laboratory. Uses for the data include but are not limited to water management, drought monitoring, energy production, health, environmental research, animal management, and crop pest management. This paper provides a technical overview and history of the network, outlining current practices for station siting, maintenance, data quality assurance, and data utility. [ABSTRACT FROM AUTHOR]

The T5 expendable bathythermographs reach the greatest depth within the current XBT family. Since the early 1970s, in several areas they have been providing a significant part of available temperature profiles below 1000 m and therefore represent an important resource for ocean climate study. In this paper we present new results from laboratory tests of Sippican T5 and T5/20 probes and analyses of more than 350 XBT–CTD matched pairs from our own field trials and the World Ocean Database (WOD), and we propose an improved fall rate equation (coefficients: A = 6.720 ± 0.025 m s−1, B = 0.001 60 ± 0.000 15 m s−2, Offset = 1.00 ± 0.65 m). Possible influences of probe physical characteristics and initial launch conditions on the probe motion have also been investigated with launching height and probe weight being identified as important factors. Analyses also confirm that fall speed and pure temperature error increase with water temperature, as previously reported for other XBT types. The uncertainties in depth and temperature measurements are then calculated. Finally, a new correction for a global T5 dataset is proposed, with an update of the currently available schemes. [ABSTRACT FROM AUTHOR]

The NOAA Tropical Atmosphere Ocean (TAO) moored array has, for three decades, been a valuable resource for monitoring and forecasting El Niño-Southern Oscillation and understanding physical oceanographic as well as coupled processes in the tropical Pacific influencing global climate. Acoustic Doppler current profiler (ADCP) measurements by TAO moorings provide benchmarks for evaluating numerical simulations of subsurface circulation including the Equatorial Undercurrent (EUC). Meanwhile, the Sea Education Association (SEA) has been collecting data during repeat cruises to the central equatorial Pacific Ocean (160°-126°W) throughout the past decade that provide useful cross validation and quantitative insight into the potential for stationary observing platforms such as TAO to incur sampling biases related to the strength of the EUC. This paper describes some essential sampling characteristics of the SEA dataset, compares SEA and TAO velocity measurements in the vicinity of the EUC, shares new insight into EUC characteristics and behavior only observable in repeat cross-equatorial sections, and estimates the sampling bias incurred by equatorial TAO moorings in their estimates of the velocity and transport of the EUC. The SEA high-resolution ADCP dataset compares well with concurrent TAO measurements (RMSE = 0.05 m s−1; R2 = 0.98), suggests that the EUC core meanders sinusoidally about the equator between ±0.4° latitude, and reveals a mean sampling bias of equatorial measurements (e.g., TAO) of the EUC's zonal velocity of −0.14 ± 0.03 m s−1 as well as a ~10% underestimation of EUC volume transport. A bias-corrected monthly record and climatology of EUC strength at 140°W for 1990-2010 is presented. [ABSTRACT FROM AUTHOR]

The recently developed two-dimensional variational methods for analyzing vortex winds from radar-observed mesocyclones can be extended to analyze three-dimensional vortex winds, but the first task for this extension is to estimate the vortex center location and its continuous variations in four-dimensional space so that the horizontal location of the vortex center can be expressed as a continuous function of height and time. To accomplish this task, a three-step method is developed in this paper. The method is applied to the Moore, Oklahoma, tornadic mesocyclone observed by the operational KTLX radar (Oklahoma City, Oklahoma) and the NSSL phased-array radar on 20 May 2013. The estimated vortex center trajectory at the ground level is verified with the tornado damage survey data. The estimated vortex center trajectories above the ground (up to 4-km height) reveal that the vortex core was initially tilted northeastward along the direction of the environmental flow and its vertical shear but became nearly vertical about 16 min later and 4 min before the vortex started to cause EF5 damages. [ABSTRACT FROM AUTHOR]

The National Oceanic and Atmospheric Administration/Earth System Research Laboratory/Chemical Sciences Division (NOAA/ESRL/CSD) has developed a versatile, airborne lidar system for measuring ozone and aerosols in the boundary layer and lower free troposphere. The Tunable Optical Profiler for Aerosol and Ozone (TOPAZ) lidar was deployed aboard a NOAA Twin Otter aircraft during the Texas Air Quality Study (TexAQS 2006) and the California Research at the Nexus of Air Quality and Climate Change (CalNex 2010) field campaigns. TOPAZ is capable of measuring ozone concentrations in the lower troposphere with uncertainties of several parts per billion by volume at 90-m vertical and 600-m horizontal resolution from an aircraft flying at 60 m s−1. The system also provides uncalibrated aerosol backscatter profiles at 18-m vertical and 600-m horizontal resolution. TOPAZ incorporates state-of-the-art technologies, including a cerium-doped lithium calcium aluminum fluoride (Ce:LiCAF) laser, to make it compact and lightweight with low power consumption. The tunable, three-wavelength UV laser source makes it possible to optimize the wavelengths for differing atmospheric conditions, reduce the interference from other atmospheric constituents, and implement advanced analysis techniques. This paper describes the TOPAZ lidar, its components and performance during testing and field operation, and the data analysis procedure, including a discussion of error sources. The performance characteristics are illustrated through a comparison between TOPAZ and an ozonesonde launched during the TexAQS 2006 field campaign. A more comprehensive set of comparisons with in situ measurements during TexAQS 2006 and an assessment of the TOPAZ accuracy and precision are presented in a companion paper. [ABSTRACT FROM AUTHOR]

Obtaining stable and accurate satellite radiances for climate change research requires extremely high standards for satellite calibration. Many satellite sensors do not currently meet the accuracy criteria, especially heritage sensors such as the Advanced Very High Resolution Radiometer (AVHRR), which shows scene temperature-dependent trends and biases of up to 0.5 K. Recently, however, a detailed study of the AVHRR/3 prelaunch data showed significant problems with both the calibration algorithm and the prelaunch data and indicated that the inherent accuracy of the AVHRR may actually be quite high. A new approach has been suggested that fixed many of the issues with the current (operational) calibration, but has not yet been applied to the in-orbit case. In this paper the behavior of the AVHRR in orbit is examined and compared to the operational AVHRR radiances from the Meteorological Operation ( MetOp)- A with those based on the new calibration to radiances derived from the Infrared Atmosphere Sounding Instrument (IASI). It is shown that the current AVHRR calibration does indeed introduce large (0.5 K) biases, but these biases are remarkably stable. It is further shown that, with some modification related to differences between the prelaunch test environment and the in-orbit environment, a physically based AVHRR calibration can match IASI to better than ~0.05 K, which is an order of magnitude better than what is currently available. Finally, it is shown that, while the new calibration is capable of providing accurate and stable radiances for the nadir view, off-nadir biases of up to 1.5 K still exist at the largest zenith angles and at the coldest scene temperatures (~210 K). For surface temperature determination, however, the scan angle bias is very small (<0.02 K), implying that the new AVHRR calibration will provide a significant improvement to, for example, sea surface temperature measurements, one of the Global Climate Observing System (GCOS)-designated essential climate variables. [ABSTRACT FROM AUTHOR]

There has been a significant increase of interest in the building of a comprehensive Arctic observing system in recent years to properly and timely track the environmental and climate processes in this vast region. In this regard, a satellite observing system on highly elliptical orbit (HEO) with 12-h period (Molniya type) is of particular interest, because it enables continuous coverage of the entire Arctic region (58°-90°N) from a constellation of two satellites. Canada is currently proposing to operate such a constellation by 2017. Extending the pioneering study of S. Q. Kidder and T. H. Vonder Haar, this paper presents in-depth analysis of spatiotemporal sampling properties of the imagery from this system. This paper also discusses challenges and advantages of this orbit for various applications that require high temporal resolution and angular sampling. [ABSTRACT FROM AUTHOR]

The 35-yr NOAA Advanced Very High Resolution Radiometer (AVHRR) observation record offers an excellent opportunity to study decadal climate variability, provided that all participating AVHRR instruments are calibrated on a consistent radiometric scale. Because of the lack of onboard calibration systems, the solar imaging channels of the AVHRR must be vicariously calibrated using invariant Earth targets as a calibrated reference source. The greatest challenge in calibrating the AVHRR dataset is the orbit degradation of the NOAA satellites, which eventually drift into a terminator orbit several years after launch. Therefore, the invariant targets must be characterized over the full range of solar zenith angles (SZAs) sampled by the satellite instrument. This study outlines a multiple invariant Earth target calibration approach specifically designed to account for the degrading NOAA orbits. The desert, polar ice, and deep convective cloud (DCC) invariant targets are characterized over all observed SZAs using NOAA-16 AVHRR measurements, which are referenced to the Aqua MODIS Collection 6 calibration via direct transfer of the MODIS calibration to the NOAA-16 AVHRR instrument using simultaneous nadir overpass (SNO) observations over the North Pole. The multiple invariant target calibrations are combined using the inverse of their temporal variance to optimize the resulting calibration stability. The NOAA-18 AVHRR gains derived using the desert, polar ice, and DCC targets, as well as from SNO, were found consistent within 1%, thereby validating that the Aqua MODIS calibration is effectively transferred to the reference calibration targets. The companion paper, Part II, applies the methodology across the AVHRR record to derive the sensor-specific calibration coefficients. [ABSTRACT FROM AUTHOR]

This paper describes a cloud type radiance record derived from NOAA polar-orbiting weather satellites using cloud properties retrieved from the Advanced Very High Resolution Radiometer (AVHRR) and spectral brightness temperatures ( T b) observed by the High Resolution Infrared Radiation Sounder (HIRS). The authors seek to produce a seamless, global-scale, long-term record of cloud type and T b statistics intended to better characterize clouds from seasonal to decadal time scales. Herein, the methodology is described in which the cloud type statistics retrieved from AVHRR are interpolated onto each HIRS footprint using two cloud classification methods. This approach is tested over the northeast tropical and subtropical Pacific Ocean region, which contains a wide variety of cloud types during a significant ENSO variation from 2008 to 2009. It is shown that the T b histograms sorted by cloud type are realistic for all HIRS channels. The magnitude of T b biases among spatially coincident satellite intersections over the northeast Pacific is a function of cloud type and wavelength. While the sign of the bias can change, the magnitudes are generally small for NOAA-18 and NOAA-19, and NOAA-19 and MetOp-A intersections. The authors further show that the differences between calculated standard deviations of cloud-typed T b well exceed intersatellite calibration uncertainties. The authors argue that consideration of higher-order statistical moments determined from spectral infrared observations may serve as a useful long-term measure of small-scale spatial changes, in particular cloud types over the HIRS-AVHRR observing record. [ABSTRACT FROM AUTHOR]

We present a new global oxygen atlas. This atlas uses all of the available full water column profiles of oxygen, salinity, and temperature available as part of the World Ocean Database released in 2018. Instead of optimal interpolation, we use the Data Interpolating Variational Analysis (DIVA) approach to map the available profiles onto 108 depth levels between the surface and 6800 m, covering more than 99% of ocean volume. This 1/2° × 1/2° atlas covers the period 1955–2018 in 1-yr intervals. The DIVA method has significant benefits over traditional optimal interpolation. It allows the explicit inclusion of advection and boundary constraints, thus offering improvements in the representations of oxygen, salinity, and temperature in regions of strong flow and near coastal boundaries. We demonstrate these benefits of this mapping approach with some examples from this atlas. We can explore the regional and temporal variations of oxygen in the global oceans. Preliminary analyses confirm earlier analyses that the oxygen minimum zone in the eastern Pacific Ocean has expanded and intensified. Oxygen inventory changes between 1970 and 2010 are assessed and compared against prior studies. We find that the full ocean oxygen inventory decreased by 0.84% ± 0.42%. For this period, temperature-driven solubility changes explain about 21% of the oxygen decline over the full water column; in the upper 100 m, solubility changes can explain all of the oxygen decrease; for the 100–600 m depth range, it can explain only 29%, 19% between 600 and 1000 m, and just 11% in the deep ocean. Significance Statement: The purpose of this study is to create a new oxygen atlas of the world's oceans using a technique that better represents the effects of ocean currents and topographic boundaries, and to investigate how oxygen in the ocean has changed over recent decades. We find the total quantity of oxygen in the world's oceans has decreased by 0.84% since 1970, similar to previous studies. We also examine how much of this change can be explained by changes in water temperature; we find that this can explain all the changes in the upper 100 m but only 21% of the oxygen decline over the whole water column. [ABSTRACT FROM AUTHOR]

Monitoring continuous changes in snowpack dynamics and its meteorological drivers is critical for understanding key aspects of water resources, climate variability, and ecology. While manual snow surveys have traditionally been used to evaluate snow processes, their high costs and discrete measurements can lead to biased estimations of accumulation and ablation rates. Ultrasonic range sensors offer an alternative to continuously monitor snow depth but their widespread employment has been limited because of high prices. This paper describes the development of an inexpensive prototype ultrasonic sensor suite characterized by a ready-to-use stand-alone design and flexibility to incorporate additional meteorological instruments. The performance of 48 units was tested during a winter season in central British Columbia, recording snow depth and air temperature data consistent with those from nearby weather stations and manual measurements. Despite a relatively small underestimation of snow depth due to known, repairable reasons, the sensor system demonstrated reliability for research and operations. [ABSTRACT FROM AUTHOR]

A method is described to calibrate a satellite microwave radiometer operating near 18–37 GHz on decadal time scales for the purposes of climate studies. The method uses stable on-earth brightness temperature references over the full dynamic range of on-earth brightness temperatures to stabilize the radiometer calibration and is applied to the Ocean Topography Experiment (TOPEX) Microwave Radiometer (TMR). These references are a vicarious cold reference, which is a statistical lower bound on ocean surface brightness temperature, and heavily vegetated, pseudoblackbody regions in the Amazon rain forest. The sensitivity of the on-earth references to climate variability is assessed. No significant climate sensitivity is found in the cold reference, as it is not sensitive to a climate minimum (e.g., coldest sea surface temperature or driest atmosphere) but arises because of a minimum in the sea surface radio brightness that occurs in the middle of the climatic distribution of sea surface temperatures (SSTs). The hot reference is observed to have a small climate dependency, which is most evident during the 1997/98 El Niño event. A time-dependent model for the hot reference region is constructed using meteorological fields from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis product. This model is shown to accurately account for the small climate variations in this reference. In addition to the long-term stabilization of the brightness temperatures, an improvement to the TMR antenna pattern correction is described that removes residual geographically correlated errors, in particular errors correlated with distance to land or sea ice. The recalibrated TMR climate data record is cross-validated with the climate data record produced from the Special Sensor Microwave Imager (SSM/I). It is shown that the intersensor drift is small, providing realistic error bars for the climate trends generated from the instrument pair, as well as validating both the methodology described in this paper and the SSM/I climate data record. [ABSTRACT FROM AUTHOR]

Characterizing the performance of ground-based commercial radiometers in cold and/or low-pressure environments is critical for developing accurate flux measurements in the polar regions and in the upper troposphere and stratosphere. Commercially available broadband radiometers have a stated operational temperature range of, typically, -20° to +50°C. Within this range, their temperature dependencies of sensitivities change less than 1%. But for deployments on high-altitude platforms or in polar regions, which can be much colder than -20°C, information on temperature dependency of sensitivity is not always available. In this paper, the temperature dependencies of sensitivities of popular pyranometers and pyrgeometers manufactured by Kipp and Zonen were tested in a thermal-vacuum chamber. When their body temperature is lowered to -60°C, pyranometer sensitivity drops by 4%–6% from the factory-default specification. Pyrgeometer sensitivity increases by 13% from the factory-default specification during a similar temperature change. When the chamber pressure is lowered from 830 to 6 hPa, the sensitivity decreases by about 2% for the pyranometer, and increases by about 2% for the pyrgeometer. Note that these temperature and pressure dependencies of sensitivities are specific for the instruments that were tested and should not be applied to others. These findings show that for measurements suitable for climate studies, it is crucial to characterize temperature and/or pressure effects on radiometer sensitivity for deployments on high-altitude platforms and in polar regions. [ABSTRACT FROM AUTHOR]

In 2004 a new aspirated surface air temperature system was officially deployed nationally in the U.S. Climate Reference Network (USCRN) commissioned by the National Oceanic and Atmospheric Administration. The primary goal of the USCRN is to provide future long-term and high-quality homogeneous observations of surface air temperature and precipitation that can be coupled to past long-term observations for the detection and attribution of present and future climate change. In this paper two precision air temperature systems are included for evaluating the new USCRN air temperature system based on a 1-yr side-by-side field comparison. The measurement errors of the USCRN temperature sensor are systematically analyzed, and the components of error attributable to the datalogger, lead wires, fixed resistors, and the temperature coefficient of the resistors are presented. Although the current configuration is adequate, a more desirable configuration of USCRN temperature sensor coupled with the datalogger is proposed as a means of further reducing the uncertainty for the USCRN temperature measurement. [ABSTRACT FROM AUTHOR]

In this paper a system for in situ measurement of H216O/H218O in air based on tunable diode laser (TDL) absorption spectroscopy is described. Laboratory tests showed that its 60-min precision (one standard deviation) was 0.21‰ at a water vapor volume mixing ratio of 2.67 mmol mol-1 (dewpoint temperature -10.8°C at sea level) and improved to 0.09 at 15.3 mmol mol-1 (dewpoint temperature 13.4°C). The TDL measurement of the vapor generated by a dewpoint generator differed from the equilibrium prediction by -0.11 ± 0.43‰ (mean ± one standard deviation). Its measurement of the ambient water vapor differed from the cold-trap/mass spectrometer method by -0.36 ± 1.43‰. The larger noise of the latter comparison was caused primarily by the difficulty in extracting vapor from air without altering its isotope content. In a 1-week test in Logan, Utah, in August 2003, the isotope ratio of water vapor in ambient air was positively correlated with the water vapor mixing ratio and also responded to wetting events (rain and irrigation) in an expected manner. This system has been in continuous operation in New Haven, Connecticut, since December 2003. It is suggested that such uninterrupted measurement may open a new window on the hydrologic cycle, particularly processes involving phase changes of water, and can increase the power of the isotope method in ecological applications. [ABSTRACT FROM AUTHOR]

Estimates of mixed layer depth are important to a wide variety of oceanic investigations including upperocean productivity, air-sea exchange processes, and long-term climate change. In the absence of direct turbulent dissipation measurements, mixed layer depth is commonly derived from oceanic profile data using threshold, integral, least squares regression, or other proxy variables. The different methodologies often yield different values for mixed layer depth. In this paper, a new method—the split-and-merge (SM) method—is introduced for determining the depth of the surface mixed layer and associated upper-ocean structure from digital conductivity-temperature-depth (CTD) profiles. Two decades of CTD observations for the continental margin of British Columbia are used to validate the SM method and to examine differences in mixed layer depth estimates for the various computational techniques. On a profile-by-profile basis, close agreement is found between the SM and de facto standard threshold methods. However, depth estimates from these two methods can differ significantly from those obtained using the integral and least squares regression methods. The SM and threshold methods are found to approximate the "true" mixed layer depth whereas the integral and regression methods typically compute the depth of the underlying pycnocline. On a statistical basis, the marginally smaller standard errors for spatially averaged mixed layer depths for the SM method suggest a slight improvement in depth determination over threshold methods. This improvement, combined with the added ability of the SM method to delineate simultaneously ancillary features of the upper ocean (such as the depth and gradient of the permanent pycnocline), make it a valuable computational tool for characterizing the structure of the upper ocean. [ABSTRACT FROM AUTHOR]

Nansen bottle casts served as the main oceanographic instrumentation type for more than a century since the establishing of the technique in the late 1890s. Between the end of the 1960s and the end of the 1990s Nansen cast technique has been gradually replaced by electronic sensor profilers (CTD). Both instrumentation types are considered as the most accurate among other oceanographic instruments and are often used as the unbiased reference. We conducted a comprehensive investigation of the consistency of the temperature data from Nansen casts and CTD profilers analyzing the quasi-collocated bottle and CTD data between the 1960s and the 1990s when both instrumentation types overlap. We found that Nansen casts tend to overestimate the sample depth with reversing mercury-in-glass thermometer temperatures being on average slightly lower compared to CTD data. Respectively, depth and temperature corrections are provided. Further, we estimated the ocean heat content changes between 1955 and 1990 using (along with all other instrumentation types) corrected and uncorrected Nansen cast data. These calculations show that for the upper 2 km layer the global average warming trend for this time period increases from 0.20 ± 0.05 W m−2 for the uncorrected data to 0.28 ± 0.06 W m−2 for the corrected data at the 90% confidence level. Finally, we suggest that the Nansen bottle cast profiles be put into a separate instrumentation group within the World Ocean Database. [ABSTRACT FROM AUTHOR]

The provision of reliable results from numerical wave models implemented over vast ocean areas can be considered as a time-consuming process. In this regard, the estimation of areas with maximum similarity in wave climate spatial areas and the determination of associated representative point locations for these areas can play an important role in climate research and in engineering applications. To deal with this issue, we apply a state-of-the-art clustering method, Geo-SOM, to determine geographical areas with similar wave regimes, in terms of mean wave direction (MWD), mean wave period (T0), and significant wave height (Hs). Although this method has many strengths, a weakness is related to detection and accounting of the most extreme and rare events. To resolve this deficiency, an initial preprocessing method (called PG-Geo-SOM) is applied. To evaluate the performance of this method, extreme wave parameters, including Hs and T0, are calculated. We simulate the present climate, represented as 1979 to 2017, compared to the future climate, 2060–98, following the Intergovernmental Panel on Climate Change (IPCC) future scenario RCP8.5 in the northwestern Atlantic Ocean. In this approach, the wave parameter data are divided into distinct groups, or clusters, motivated by their geographical positions. For each cluster, the centroid spatial point and the time series of data are extracted, for Hs, MWD, and T0. Extreme values are estimated for 5-, 10-, 25-, 50-, and 100-yr return periods, using Gumbel, exponential, and Weibull stochastic models, for both present and future climates. Results show that for parameter T0, the impact of climate change for the study area is a decreasing trend, while for Hs, in coastal and shelf areas up to about 1000 km from the coastline, increasing trends are estimated, and in open-ocean areas, far from the coast, decreasing trends are obtained. [ABSTRACT FROM AUTHOR]

Expendable bathythermographs (XBTs) have been widely deployed for ocean monitoring since the late 1960s. Improving the quality of XBT data is a vital task in climatology. Many factors (e.g., temperature, probe type, and manufacturing time) have been identified as major influences of XBT systematic bias. In addition, the recording system (RS) has long been suspected as another factor. However, this factor has not been taken into account in any global XBT correction schemes, partly because its impact is poorly understood. Here, based on analysis of an XBT–CTD side-by-side dataset and a global collocated reference dataset, the influence of RSs on the pure temperature error (PTE) is examined. Results show a clear time dependency of PTE on the RS, with maximum values occurring in the 1970s. In addition, the method used to convert thermistor resistance into temperature in the RS (using a resistance–temperature equation) has changed over time. These changes, together with the decadal changes in RSs, might contribute a small error (10% on average) to the RS dependency. Here, an improvement of global XBT bias correction that accounts for the RS dependency is proposed. However, more than 70% of historical global XBT data are missing RS-type information. We investigate several assumptions about the temporal distribution of RS types, and all scenarios lead to at least a ~50% reduction in the time variation of PTE compared with the uncorrected data. Therefore, the RS dependency should be taken into account in updated XBT correction schemes, which would have further implications for climatology studies. [ABSTRACT FROM AUTHOR]

Snow depth is an important geophysical variable for investigating sea ice and climate change, which can be obtained from satellite data. However, there is a large number of missing data in satellite observations of snow depth. In this study, a methodology, the periodic functions fitting with varying parameter (PFF-VP), is presented to fit the time series of snow depth on Arctic sea ice obtained from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E). The time-varying parameters are obtained by the independent point (IP) scheme and cubic spline interpolation. The PPF-VP is validated by experiments in which part of the observations are artificially removed and used to compare with the fitting results. Results indicate that the PPF-VP performs better than three traditional fitting methods, with its fitting results closer to observations and with smaller errors. In the practical experiments, the optimal number of IPs can be determined by only considering the fraction of missing data, particularly the length of the longest gaps in the snow-depth time series. All the experimental results indicate that the PPF-VP is a feasible and effective method to fit the time series of snow depth and can provide continuous data of snow depth for further study. [ABSTRACT FROM AUTHOR]

Screen-level air temperature measurements at surface observation stations are influenced by local-site-scale factors. These local influences may affect global-scale climate change studies. This study investigated the influence of surface obstacles on air temperature measurements at the screen level at climate observation stations in Japan. Screen-level air temperature was measured simultaneously at two neighboring sites (<100 m apart) that differed in terms of their openness. Daytime air temperature was 0°–1°C higher at the narrower site, and theoretical analysis revealed that this warming was caused by poor ventilation. At night, poor ventilation at the narrower site caused the air temperature to be 0°–0.2°C lower, which was demonstrated experimentally and by theoretical analysis. The range of temperature changes due to site narrowing shown in this study is not negligible in climate change studies. Guidelines for site maintenance and metadata recoding were consequently proposed in terms of site openness. [ABSTRACT FROM AUTHOR]

Researchers now have the benefit of an unprecedented suite of space- and ground-based sensors that provide multidimensional and multiparameter precipitation information. Motivated by NASA's Global Precipitation Measurement (GPM) mission and ground validation objectives, the System for Integrating Multiplatform Data to Build the Atmospheric Column (SIMBA) has been developed as a unique multisensor precipitation data fusion tool to unify field observations recorded in a variety of formats and coordinate systems into a common reference frame. Through platform-specific modules, SIMBA processes data from native coordinates and resolutions only to the extent required to set them into a user-defined three-dimensional grid. At present, the system supports several ground-based scanning research radars, NWS NEXRAD radars, profiling Micro Rain Radars (MRRs), multiple disdrometers and rain gauges, soundings, the GPM Microwave Imager and Dual- Frequency Precipitation Radar on board the Core Observatory satellite, and Multi-Radar Multi-Sensor system quantitative precipitation estimates. SIMBA generates a new atmospheric column data product that contains a concomitant set of all available data from the supported platforms within the user-specified grid defining the column area in the versatile netCDF format. Key parameters for each data source are preserved as attributes. SIMBA provides a streamlined framework for initial research tasks, facilitating more efficient precipitation science. We demonstrate the utility of SIMBA for investigations, such as assessing spatial precipitation variability at subpixel scales and appraising satellite sensor algorithm representation of vertical precipitation structure for GPM Core Observatory overpass cases collected in the NASAWallops Precipitation Science Research Facility and the GPM Olympic Mountain Experiment (OLYMPEX) ground validation field campaign in Washington State. [ABSTRACT FROM AUTHOR]

Precipitation observation with the Tropical Rainfall Measuring Mission's (TRMM's) precipitation radar (PR) lasted for more than 17 years. To study the changes in the water and energy cycle related to interannual and decadal variabilities of climate, homogeneity of long-term PR data is essential. The aim of the study is to develop a precipitation climate record from the 17-yr PR observation. The focus was on mitigating the discontinuities associated with the switching to redundant electronics in the PR in June 2009. In version 7 of the level-1 PR product, a discontinuity in noise power is found at this timing, indicating a change in the signal-to-noise ratio. To mitigate the effect of this discontinuity on climate studies, the noise power of the B-side PR obtained after June 2009 is artificially increased to match that of the A-side PR. Simulation results show that the storm height and the precipitation frequency detected by the PR relatively decrease by 2.17% and 5.15% in the TRMM coverage area (35°S-35°N), respectively, and that the obvious discontinuity of the time series by the storm height and the precipitation fraction caused by the switching to the redundancy electronics is mitigated. Differences in the statistics of other precipitation parameters caused by the switching are also mitigated. The unconditional precipitation rate derived from the adjusted data obtained over the TRMM coverage area decreases by 0.90% as compared with that determined from the original data. This decrease is mainly caused by reductions in the detection of light precipitation. [ABSTRACT FROM AUTHOR]

Historical reconstructions of climate fields, such as sea surface temperature (SST), are important for climate studies and monitoring. Reconstructions use statistics from a well-sampled base period to analyze a sparsely sampled historical period. Here a method is shown for adjusting the base-period statistics using the available historical data so that statistics better represent historical variations. The method is demonstrated using annual SST anomalies from a coupled GCM historical run, 1861-2005, forced by greenhouse gases and aerosols. Simulated data are constructed from the model's SST using observed historical SST sampling with error estimates added. Reconstructions are performed using the simulated data, and the results are compared to the full model SST without added errors. The results from applying other reconstruction methods to the simulated data are compared. The tests show that the method improves annual SST reconstructions, especially in the early years, when sampling is most sparse and in the extratropics. In particular, the 1881-1900 correlation averaged over 30°-60°S and over 30°-60°N improves from about 0.4 using noniterative reconstruction to about 0.6 using iterative reconstruction. The correlations of annual values in the tropics are about 0.7 with both methods. Incorporating those improvements into an SST reconstruction could better represent extratropical climate variations in the nineteenth and early twentieth centuries, and improve the value of the reconstruction for long-period climate studies and for validating climate models. [ABSTRACT FROM AUTHOR]

The Advanced Microwave Sounding Unit-A (AMSU-A, 1998-present) not only continues but surpasses the Microwave Sounding Unit's (MSU, 1978-2006) capability in atmospheric temperature observation. It provides valuable satellite measurements for higher vertical resolution and long-term climate change research and trend monitoring. This study presented methodologies for generating 11 channels of AMSU-A-only atmospheric temperature data records from the lower troposphere to the top of the stratosphere. The recalibrated AMSU-A level 1c radiances recently developed by the Center for Satellite Applications and Research group were used. The recalibrated radiances were adjusted to a consistent sensor incidence angle (nadir), channel frequencies (prelaunch-specified central frequencies), and observation time (local solar noon time). Radiative transfer simulations were used to correct the sensor incidence angle effect and the National Oceanic and Atmospheric Administration-15 ( NOAA-15) channel 6 frequency shift. Multiyear averaged diurnal/semidiurnal anomaly climatologies from climate reanalysis as well as climate model simulations were used to adjust satellite observations to local solar noon time. Adjusted AMSU-A measurements from six satellites were carefully quality controlled and merged to generate 13+ years (1998-2011) of a monthly 2.5° × 2.5° gridded atmospheric temperature data record. Major trend features in the AMSU-A-only atmospheric temperature time series, including global mean temperature trends and spatial trend patterns, were summarized. [ABSTRACT FROM AUTHOR]

Two different cloud climatologies have been derived from the same NASA-Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP)-measured attenuated backscattered profile (level 1, version 3 dataset). The first climatology, named Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations-Science Team ( CALIPSO-ST), is based on the standard CALIOP cloud mask (level 2 product, version 3), with the aim to document clouds with the highest possible spatiotemporal resolution, taking full advantage of the CALIOP capabilities and sensitivity for a wide range of cloud scientific studies. The second climatology, named GCM-Oriented CALIPSO Cloud Product ( CALIPSO-GOCCP), is aimed at a single goal: evaluating GCM prediction of cloudiness. For this specific purpose, it has been designed to be fully consistent with the CALIPSO simulator included in the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) used within version 2 of the CFMIP (CFMIP-2) experiment and phase 5 of the Coupled Model Intercomparison Project (CMIP5). The differences between the two datasets in the global cloud cover maps-total, low level ( P > 680 hPa), midlevel (680 < P < 440 hPa), and high level ( P < 440 hPa)-are frequently larger than 10% and vary with region. The two climatologies show significant differences in the zonal cloud fraction profile (which differ by a factor of almost 2 in some regions), which are due to the differences in the horizontal and vertical averaging of the measured attenuated backscattered profile CALIOP profile before the cloud detection and to the threshold used to detect clouds (this threshold depends on the resolution and the signal-to-noise ratio). [ABSTRACT FROM AUTHOR]

Near-real-time quality control procedures for temperature profiles collected from ships of opportunity were implemented during the 1980s in oceans across the world and from the 1990s in the Mediterranean. In this sea, the procedures were originally based on seven steps (detection of end of profile, gross range check, position control, elimination of spikes, Gaussian smoothing and resampling at 1-m intervals, general malfunction control, and comparison with climatology), complemented with initial and final visual checks. The quality of data derived from a comparison with historical data (namely, climatology) depends on the availability of a huge amount of data that can statistically represent the mean characteristics of the seawater. A significant amount of data has been collected, and the existing temperature database in the Mediterranean can now provide more information on temporal and spatial variability at monthly and mesoscales, and an improved procedure for data quality control has now been adopted. New 'best' estimates of monthly temperature profiles are calculated by using a maximum likelihood method. It has been found that more than one 'best estimate' temperature can be defined in particular areas and depths, as a consequence of climate variability. Additional near-real-time control procedures have been included in order to provide information on long-term variability associated with data. This information is included in metafiles to be used for reanalysis and studies on long-term variability and changes. [ABSTRACT FROM AUTHOR]

A radio occultation data processing system (OCC) was developed for numerical weather prediction and climate benchmarking. The data processing algorithms use the well-established Fourier integral operator--based methods, which ensure a high accuracy of retrievals. The system as a whole, or in its parts, is currently used at the Global Navigation Satellite System Receiver for Atmospheric Sounding (GRAS) Satellite Application Facility at the Danish Meteorological Institute, German Weather Service, and Wegener Center for Climate and Global Change. A statistical comparison of the inversions of the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) data by the system herein, University Corporation for Atmospheric Research (UCAR) data products, and ECMWF analyses is presented. Forty days of 2007 and 2008 were processed (from 5 days in the middle of each season) for the comparison of OCC and ECMWF, and 20 days of April 2009 were processed for the comparison of OCC, UCAR, and ECMWF. The OCC and UCAR inversions are consistent. For the tropics, the systematic difference between OCC and UCAR in the retrieved refractivity in the 2--30-km height interval does not exceed 0.1%%; in particular, in the 9--25-km interval it does not exceed 0.03%%. Below 1 km in the tropics the OCC -- UCAR bias reaches 0.2%%, which is explained by different cutoff and filtering schemes implemented in the two systems. The structure of the systematic OCC -- ECMWF difference below 4 km changes in 2007, 2008, and 2009, which is explained by changes in the ECMWF analyses and assimilation schemes. It is estimated that in the 4--30-km height range the OCC occultation processing system obtains refractivities with a bias not exceeding 0.2%%. The random error ranges from 0.3%%--0.5%% in the upper troposphere--lower stratosphere to about 2%% below 4 km. The estimate of the bias below 4 km can currently be done with an accuracy of 0.5%%--1%% resulting from the structural uncertainty of the radio occultation (RO) data reflecting the insufficient knowledge of the atmospheric small-scale structures and instrumental errors. The OCC -- UCAR bias is below the level of the structural uncertainty. [ABSTRACT FROM AUTHOR]

The Estimating the Circulation and Climate of the Ocean (ECCO) consortium provides a framework in which the adjoint method of data assimilation is applied to a general circulation model to provide a dynamically self-consistent estimate of the time-varying ocean state, which is constrained by observations. In this study, the sensitivity of the solution to the constraints provided by various datasets is investigated in a regional setting in the North Pacific. Four assimilation experiments are performed, which vary by the data used as constraints and the relative weights associated with these data. The resulting estimates are compared to two of the assimilated datasets as well as to data from two time series stations not used as constraints. These comparisons demonstrate that increasing the weights of the subsurface data provides overall improvement in the model–data consistency of the estimate of the state of the North Pacific Ocean. However, some elements of the solution are degraded. This could result from incompatibility between datasets, possibly because of hidden biases, or from errors in the model physics made more evident by the increased weight on subsurface data. The adjustments to the control parameters of surface forcing and initial conditions necessary to obtain the more accurate fit to the data are found to be within prior error bars. [ABSTRACT FROM AUTHOR]

Spaceborne measurements pinned to international standards are needed to monitor the earth’s climate, quantify human influence thereon, and test forecasts of future climate change. The International System of Units (SI, from the French for Système International d’Unités) provides ideal measurement standards for radiometry as they can be realized anywhere, at any time in the future. The challenge is to credibly prove on-orbit accuracy at a claimed level against these international standards. The most accurate measurements of thermal infrared spectra are achieved with blackbody-based calibration. Thus, SI-traceability is obtained through the kelvin scale, making thermometry the foundation for on-orbit SI-traceable spectral infrared measurements. Thermodynamic phase transitions are well established as reproducible temperature standards and form the basis of the international practical temperature scale (International Temperature Scale of 1990, ITS-90). Appropriate phase transitions are known in the temperature range relevant to thermal infrared earth observation (190–330 K) that can be packaged such that they are chemically stable over the lifetime of a space mission, providing robust and traceable temperature calibrations. A prototype blackbody is presented that is compact, highly emissive, thermally stable and homogeneous, and incorporates a small gallium melting point cell. Precision thermal control of the blackbody allows the phase transition to be identified to within 5 mK. Based on these results, the viability of end-to-end thermometric calibration of both single-temperature and variable-temperature blackbodies on orbit by employing multiple-phase-change cells was demonstrated. [ABSTRACT FROM AUTHOR]

In this study, a penalized maximal F test (PMFT) is proposed for detecting undocumented mean shifts that are not accompanied by any sudden change in the linear trend of time series. PMFT aims to even out the uneven distribution of false alarm rate and detection power of the corresponding unpenalized maximal F test that is based on a common-trend two-phase regression model (TPR3). The performance of PMFT is compared with that of TPR3 using Monte Carlo simulations and real climate data series. It is shown that, due to the effect of unequal sample sizes, the false alarm rate of TPR3 has a W-shaped distribution, with much higher than specified values for points near the ends of the series and lower values for points between either of the ends and the middle of the series. Consequently, for a mean shift of certain magnitude, TPR3 would detect it with a lower-than-specified level of confidence and hence more easily when it occurs near the ends of the series than somewhere between either of the ends and the middle of the series; it would mistakenly declare many more changepoints near the ends of a homogeneous series. These undesirable features of TPR3 are diminished in PMFT by using an empirical penalty function to take into account the relative position of each point being tested. As a result, PMFT has a notably higher power of detection; its false alarm rate and effective level of confidence are very close to the nominal level, basically evenly distributed across all possible candidate changepoints. The improvement in hit rate can be more than 10% for detecting small shifts (Δ ≤ σ, where σ is the noise standard deviation). [ABSTRACT FROM AUTHOR]

TempVal is a spatial component of data quality assurance algorithms applied by the National Climatic Data Center (NCDC), and it has been used operationally for about 4 yr. A spatial regression test (SRT) approach was developed at the regional climate centers for climate data quality assurance and was found to be superior to currently used quality control (QC) procedures for the daily maximum and minimum air temperature. The performance of the spatial quality assessment procedures has been evaluated by assessing the rate with which seeded errors are identified. A complete dataset with seeded errors for the year 2003 for the contiguous United States was examined for both the maximum and minimum air temperature. The spatial regression quality assessment component (SRT), originating in the Automated Climate Information System (ACIS), and TempVal, originating in the NCDC database, were applied separately and evaluated through the ratio of identified seeded errors to the total number of seeds. The spatial regression test applied in the ACIS system was found to perform better in identifying the seeded errors. For all months, the relative frequency of correct identification of wrong data is 0.72 and 0.83 for TempVal and SRT, respectively. The goal of the comparison was to evaluate quality assurance techniques that could improve data quality assessment at the NCDC, and the results of the comparison led to the recommendation that the SRT be included in the NCDC quality assessment methodology. [ABSTRACT FROM AUTHOR]

Near-surface bulk water temperature measured in large northern lakes during the warm season with buoys can be characterized by three components: a slowly varying seasonal-/climate-related trend, fluctuations at the time scale of weather perturbations, and rapid daily fluctuations. When thermal infrared data are used to estimate surface water temperature, an additional term relating the differences between the skin and bulk temperatures is implied. Buoy data in this work serve to demonstrate the existence of a period of strong signal coupling between fluctuations of water temperature and air temperature. The period of strong signal coupling does not extend beyond the date of maximum temperature in the water temperature trend. During this period, a simple linear transformation of air temperature fluctuations can be used to simulate the buoy water temperature fluctuations. Attempts to simulate water temperature fluctuations from air temperature alone are not possible beyond this period. Water temperature simulation error depends on the distance of the air temperature measurement from the buoy, ranging from ±1.1°C at 0 km to ±1.4°C at 40 km. The method developed with buoy data is applied to the combination of satellite thermal infrared and operationally measured air temperature data to simulate water temperatures. Through the use of satellite data, the water temperature simulations are extended beyond the period of strong coupling. [ABSTRACT FROM AUTHOR]

There is an increasing interest in examining long-term trends in measures of snow climatology. An examination of the U.S. daily snowfall records for 1900–2004 revealed numerous apparent inconsistencies. For example, long-term snowfall trends among neighboring lake-effect stations differ greatly from insignificant to +100% century-1. Internal inconsistencies in the snow records, such as a lack of upward trends in maximum seasonal snow depth at stations with large upward trends in snowfall, point to inhomogeneities. Nationwide, the frequency of daily observations with a 10:1 snowfall-to-liquid-equivalent ratio declined from 30% in the 1930s to a current value of around 10%, a change that is clearly due to observational practice. There then must be biases in cold-season liquid-equivalent precipitation, or snowfall, or both. An empirical adjustment of snow-event, liquid-equivalent precipitation indicates that the potential biases can be statistically significant. Examples from this study show that there are nonclimatic issues that complicate the identification of and significantly change the trends in snow variables. Thus, great care should be taken in interpretation of time series of snow-related variables from the Cooperative Observer Program (COOP) network. Furthermore, full documentation of optional practices should be required of network observers so that future users of these data can properly account for such practices. [ABSTRACT FROM AUTHOR]

Various interests desire information and data on heavy snowfalls to define their spatial and temporal occurrences. Historical data at the nation’s 208 first-order stations for events with 15.2 cm or more snowfall in 2 days or less was assessed, and revealed various serious data problems at 118 stations with climatological quality data available for 90 stations. The data problems are described as guidelines for those seeking to utilize heavy snowfall data, and stations with quality data are listed. [ABSTRACT FROM AUTHOR]

All long historical climate records are based on measurements that experienced shifts in instrumentation, site characteristics, or locations. How such changes affect the quality of past data remains an uncertainty for the thousands of historical records, confounding efforts to assess climate change. Fortunately, one station in Illinois with 118 yr of records has also kept detailed records of all such shifts plus overlapping measurements of temperatures and precipitation, allowing exact measurements of how conditions changed over time. This study examined these data and found varying discontinuities of 0.1°–0.9°C in annual temperatures due to various shifts, but no changes in daily precipitation related to site shifts. However, hourly precipitation amounts from recording rain gauges did undergo a considerable shift due to changes in rain gauge types. Similar studies need to be made of other stations with comparable historical records of station and instrument shifts and with overlapping measurements when shifts were made. [ABSTRACT FROM AUTHOR]

To assess climatic changes in sea surface temperature (SST), changes in the measurement method with time and the effect of these changes on the mean SST must be quantified. Observations from the International Comprehensive Ocean–Atmosphere Data Set (ICOADS) have been analyzed for the period from 1970 to 1997 using both SST measurement metadata contained within the dataset and a World Meteorological Organization (WMO) catalog of observing ships. The WMO metadata were particularly important in identifying engine-intake SSTs during the 1970s, but increased method identification over the entire period. There are strong regional variations in the preferred SST measurement method, with engine-intake SST most common in the Pacific and bucket SST preferred by countries bordering the Atlantic. The number of engine-intake SSTs increases over time and becomes more numerous than buckets by the early 1980s. There are significant differences between SST observations made by different methods. The rounding of reports is more common for engine-intake SST than for either bucket or hull sensor SST, which degrades its quality. Significant time-varying biases exist between SST derived from buckets and from engine intakes. The SST difference has a strong seasonal signal with bucket SST being relatively cold in winter, probably resulting from heat loss from the buckets, and warm in summer, probably resulting from solar warming or the sampling of a shallow warm layer. There is also a long-term trend with engine-intake SST being relatively warm in the early period but with a small annual mean difference between the two methods by 1990. [ABSTRACT FROM AUTHOR]

Atmospheric radiation flux measurements and the resulting surface radiation budget are important quantities for greenhouse effect and climate change investigations. Accurate net shortwave and longwave fluxes, in conjunction with numerical algorithms, also allow monitoring of the radiative effect of clouds and the nowcasting of the cloud amount. To achieve certain advantages on the accuracy of flux measurements a new instrument is developed that measures downward and upward shortwave and longwave radiation with the same sensors. Two high-quality instruments—a pyranometer for shortwave and a pyrgeometer for longwave measurements—are mounted on a pivotable sensor head, which is rotated up and down in 10-min intervals. To keep the instrument domes free from dew and ice, and to minimize the pyranometer thermal offset, both sensors are ventilated with slightly heated air. Additionally, a ventilated temperature and humidity sensor is integrated in the new instrument. The combination of measurements of radiation fluxes, temperature, and humidity allows for instrument use for autonomous and automatic cloud amount detection. The Temperature, Humidity, Radiation and Clouds (TURAC) sensor has been successfully tested under harsh alpine winter conditions, as well as under moderate lowland conditions. Comparisons to reference instruments showed all radiation fluxes to be within a maximum bias and rms difference of 1.6% or 1.4 W m-2 on daily averages. [ABSTRACT FROM AUTHOR]

Passive microwave rainfall estimates that exploit the emission signal of raindrops in the atmosphere are sensitive to the inhomogeneity of rainfall within the satellite field of view (FOV). In particular, the concave nature of the brightness temperature (Tb) versus rainfall relations at frequencies capable of detecting the blackbody emission of raindrops cause retrieval algorithms to systematically underestimate precipitation unless the rainfall is homogeneous within a radiometer FOV, or the inhomogeneity is accounted for explicitly. This problem has a long history in the passive microwave community and has been termed the beam-filling error. While not a true error, correcting for it requires a priori knowledge about the actual distribution of the rainfall within the satellite FOV, or at least a statistical representation of this inhomogeneity. This study first examines the magnitude of this beam-filling correction when slant-path radiative transfer calculations are used to account for the oblique incidence of current radiometers. Because of the horizontal averaging that occurs away from the nadir direction, the beam-filling error is found to be only a fraction of what has been reported previously in the literature based upon plane-parallel calculations. For a FOV representative of the 19-GHz radiometer channel (18 km × 28 km) aboard the Tropical Rainfall Measuring Mission (TRMM), the mean beam-filling correction computed in this study for tropical atmospheres is 1.26 instead of 1.52 computed from plane-parallel techniques. The slant-path solution is also less sensitive to finescale rainfall inhomogeneity and is, thus, able to make use of 4-km radar data from the TRMM Precipitation Radar (PR) in order to map regional and seasonal distributions of observed rainfall inhomogeneity in the Tropics. The data are examined to assess the expected errors introduced into climate rainfall records by unresolved changes in rainfall inhomogeneity. Results show that global mean monthly errors introduced by not explicitly accounting for rainfall inhomogeneity do not exceed 0.5% if the beam-filling error is allowed to be a function of rainfall rate and freezing level and does not exceed 2% if a universal beam-filling correction is applied that depends only upon the freezing level. Monthly regional errors can be significantly larger. Over the Indian Ocean, errors as large as 8% were found if the beam-filling correction is allowed to vary with rainfall rate and freezing level while errors of 15% were found if a universal correction is used. [ABSTRACT FROM AUTHOR]

In situ and autonomous measurements of sea surface temperature (SST) have been performed with a thermal infrared radiometer mounted on a fixed oil rig. The accuracy limit was established at ±0.3 K for these SST measurements in order to meet the requirements of the Tropical Ocean Global Atmosphere (TOGA) program for global climate research and the Soil Moisture and Ocean Salinity (SMOS) mission for salinity retrieval. With this aim, the optimal observation angle and spectral channel for SST measurements have been identified. Then, a methodology has been developed for the radiometer calibration and the emissivity correction, including the reflection of the downwelling sky radiance, which was directly measured simultaneously to the sea surface observation. The effect of the atmospheric path between the sea surface and the sensor has been also studied and found negligible for the particular viewing conditions. A sensitivity analysis of the proposed methodology has shown a precision of ±0.15 K in the retrieved SST. Finally, the measured SSTs have been validated with coincident buoy temperatures, resulting in an average difference of 0.0 K and a standard deviation of ±0.2 K. [ABSTRACT FROM AUTHOR]

The importance of atmospheric aerosols in understanding global climate changes has renewed interest in measurements of cloud condensation nuclei (CCN). To obtain high-resolution (125 m) vertical profiles of CCN number concentration, a balloon-borne instrument was developed. The instrument deduces the CCN concentration from measurements of laser light scattered by water droplets that condense on CCN within a static thermal-gradient diffusion chamber. The amount of light scattering is linearly proportional to the number of droplets within the diffusion chamber. Correlating the number of droplets within the sample volume with the amount of light scattered by the droplets provides the calibration constant that relates scattered light to CCN concentration. The calibration was tested by comparisons between the CCN counter and a condensation nuclei counter when sampling monodisperse aerosol larger than the CCN counter's critical activation size. The calibration constant depends on supersaturation, and depends slightly on the size of CCN that activate to form droplets. For dry NaCl aerosol between 35 and 160 nm, the calibration constant varies by less than 10% at 1% supersaturation. Calibration on ambient atmospheric aerosol is similar to calibration on laboratory-generated polydisperse NaCl aerosol, which indicates that the laboratory calibration can be applied to field measurements. During field and laboratory measurements, the time required for the activation and growth of droplets within the diffusion chamber is similar. Overall, the uncertainty of the calibration constant for the balloon-borne CCN counter is approximately 10% at 1% supersaturation. [ABSTRACT FROM AUTHOR]

Pressure measurements made in two turbid natural waters have led to the inference that the effective depth-mean in situ density values, reff , of these waters are less than (≈2.70%--6.5%) their bulk densities (i.e., densities of water--sediment mixture), and also less than (≈0.4%--4.5%) that of the density of the same water after removal of suspended sediment. The values of reff in a given site differed from one tidal cycle to another (≈1.9%). These values varied slightly (,0.8%) from midtide to slack water period of the same tidal cycle, with reff being lower at midtide. It was found that the use of bulk density to estimate tidal elevation yielded an underestimation of tidal range (up to 7%). The underestimation has been corrected (to within 61.5%) with the use of reff parameter. For clear waters there was no measurable underestimation in tidal range. The observations indicate an apparent in situ density reduction for turbid natural waters. With the use of two pressure transducers at a known vertical separation, the value of reff over this vertical column of water may be determined during each sampling of pressure values. The present studies indicate that when pressure transducers are used for water level measurements in turbid natural waters, the use of reff , in contrast to the bulk density, significantly improves the measurement accuracy. For clear waters, precision density measurements made on discrete water samples agreed with reff values derived from pressure measurements to better than 60.4%. Thus, use of reff is expected to improve the accuracy of water level measurements also from clear water estuaries where depth-mean water density undergoes marginal changes with differing phases of tide and significant changes with seasons. [ABSTRACT FROM AUTHOR]