Mid-infrared filters for astronomical and remote sensing instrumentation

As improvements to the optical design of spectrometer and radiometer instruments evolve with advances in detector sensitivity, use of focal plane detector arrays and innovations in adaptive optics for large high altitude telescopes, interest in mid-infrared astronomy and remote sensing applications have been areas of progressive research in recent years. This research has promoted a number of developments in infrared coating performance, particularly by placing increased demands on the spectral imaging requirements of filters to precisely isolate radiation between discrete wavebands and improve photometric accuracy. The spectral design and construction of multilayer filters to accommodate these developments has subsequently been an area of challenging thin-film research, to achieve high spectral positioning accuracy, environmental durability and aging stability at cryogenic temperatures, whilst maximizing the far-infrared performance. In this paper we examine the design and fabrication of interference filters in instruments that utilize the mid-infrared N-band (6-15 µm) and Q-band (16-28 µm) atmospheric windows, together with a rationale for the selection of materials, deposition process, spectral measurements and assessment of environmental durability performance.

Design and fabrication of infrared filters for remote sounding instrumentation

Cooled infrared filters have been used in pressure modulation and filter radiometry to measure the dynamics, temperature distribution and concentrations of atmospheric elements in various satellite radiometers. Invariably such instruments use precision infrared bandpass filters and coatings for spectral selction, often operating at cryogenic temperatures. More recent developments in the use of spectrally-selective cooled detectors in focal plane arrays have simplified the optical layout and reduced the component count of radiometers but have placed additional demands on both the spectral and physical performance requirements of the filters. This paper describes and contrasts the more traditional radiometers using discrete detectors with those which use focal plane detector array technology, with particular emphasis on the function of the filters and coatings in the two cases. Additionally we discuss the spectral techniques and materials used to fabricate infrared coatings and filters for use in space optics, and give examples of their application in the fabrication of some demanding long wavelength dichroics and filters. We also discuss the effects of the space environment on the stability and durability of high performance infrared filters and materials exposed to low Earth orbit for 69 months on the NASA Long Duration Exposure Facility (LDEF).

An improved algorithm for generating global window brightness temperatures from multiple satellite infrared imagery

An improved algorithm for the generation of gridded window brightness temperatures is presented. The primary data source is the International Satellite Cloud Climatology Project, level B3 data, covering the period from July 1983 to the present. The algorithm rakes window brightness, temperatures from multiple satellites, both geostationary and polar orbiting, which have already been navigated and normalized radiometrically to the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer, and generates 3-hourly global images on a 0.5 degrees by 0.5 degrees latitude-longitude grid. The gridding uses a hierarchical scheme based on spherical kernel estimators. As part of the gridding procedure, the geostationary data are corrected for limb effects using a simple empirical correction to the radiances, from which the corrected temperatures are computed. This is in addition to the application of satellite zenith angle weighting to downweight limb pixels in preference to nearer-nadir pixels. The polar orbiter data are windowed on the target time with temporal weighting to account for the noncontemporaneous nature of the data. Large regions of missing data are interpolated from adjacent processed images using a form of motion compensated interpolation based on the estimation of motion vectors using an hierarchical block matching scheme. Examples are shown of the various stages in the process. Also shown are examples of the usefulness of this type of data in GCM validation.

Influence of south Atlantic sea surface temperatures on rainfall variability and extremes over southern Africa

It is generally agreed that changing climate variability, and the associated change in climate extremes, may have a greater impact on environmentally vulnerable regions than a changing mean. This research investigates rainfall variability, rainfall extremes, and their associations with atmospheric and oceanic circulations over southern Africa, a region that is considered particularly vulnerable to extreme events because of numerous environmental, social, and economic pressures. Because rainfall variability is a function of scale, high-resolution data are needed to identify extreme events. Thus, this research uses remotely sensed rainfall data and climate model experiments at high spatial and temporal resolution, with the overall aim being to investigate the ways in which sea surface temperature (SST) anomalies influence rainfall extremes over southern Africa. Extreme rainfall identification is achieved by the high-resolution microwave/infrared rainfall algorithm dataset. This comprises satellite-derived daily rainfall from 1993 to 2002 and covers southern Africa at a spatial resolution of 0.1° latitude–longitude. Extremes are extracted and used with reanalysis data to study possible circulation anomalies associated with extreme rainfall. Anomalously cold SSTs in the central South Atlantic and warm SSTs off the coast of southwestern Africa seem to be statistically related to rainfall extremes. Further, through a number of idealized climate model experiments, it would appear that both decreasing SSTs in the central South Atlantic and increasing SSTs off the coast of southwestern Africa lead to a demonstrable increase in daily rainfall and rainfall extremes over southern Africa, via local effects such as increased convection and remote effects such as an adjustment of the Walker-type circulation.

Multidecadal modulation of El Nino-Southern Oscillation (ENSO) variance by Atlantic Ocean sea surface temperatures

Observations suggest a possible link between the Atlantic Multidecadal Oscillation (AMO) and El Nino Southern Oscillation (ENSO) variability, with the warm AMO phase being related to weaker ENSO variability. A coupled ocean-atmosphere model is used to investigate this relationship and to elucidate mechanisms responsible for it. Anomalous sea surface temperatures (SSTs) associated with the positive AMO lead to change in the basic state in the tropical Pacific Ocean. This basic state change is associated with a deepened thermocline and reduced vertical stratification of the equatorial Pacific ocean, which in turn leads to weakened ENSO variability. We suggest a role for an atmospheric bridge that rapidly conveys the influence of the Atlantic Ocean to the tropical Pacific. The results suggest a non-local mechanism for changes in ENSO statistics and imply that anomalous Atlantic ocean SSTs can modulate both mean climate and climate variability over the Pacific.

Natural ventilation effects on temperatures within Stevenson screens

Thermometer screen properties are poorly characterised at low wind speeds. Temperatures from a large thermometer screen have been compared with those from an automatically shaded open-air fine-wire resistance thermometer. For the majority of 5-minute average measurements obtained between July 2008 and 2009, the screen and fine-wire temperatures agreed closely, with a median difference <0.05◦C. At low wind speeds however, larger temperature differences occurred. When calm (wind speed at 2 metres, u2, ≤ 0.1 m s−1), the difference between screen and open-air temperatures varied from −0.25◦C to +0.87◦C. At night with u2 < 0.5 m s−1, this difference was −0.14◦C to 0.39◦C, and, rarely, up to −0.68◦C to 1.38◦C. At the minimum in the daily temperature cycle, the semi-urban site at Reading had u2 < 1 m s−1 for 52% of the observations 1997–2008, u2 < 0.5 m s−1 for 34% and calm conditions for 20%. Consequently uncertainties in the minimum temperature measurements may arise from poor ventilation, which can propagate through calculations to daily average temperatures. In comparison with the daily minimum temperature, the 0900 UTC synoptic temperature measurement has a much lower abundance (5%) of calm conditions.

When can we expect extremely high surface temperatures?

In the Essence project a 17-member ensemble simulation of climate change in response to the SRES A1b scenario has been carried out using the ECHAM5/MPI-OM climate model. The relatively large size of the ensemble makes it possible to accurately investigate changes in extreme values of climate variables. Here we focus on the annual-maximum 2m-temperature and fit a Generalized Extreme Value (GEV) distribution to the simulated values and investigate the development of the parameters of this distribution. Over most land areas both the location and the scale parameter increase. Consequently the 100-year return values increase faster than the average temperatures. A comparison of simulated 100-year return values for the present climate with observations (station data and reanalysis) shows that the ECHAM5/MPI-OM model, as well as other models, overestimates extreme temperature values. After correcting for this bias, it still shows values in excess of 50°C in Australia, India, the Middle East, North Africa, the Sahel and equatorial and subtropical South America at the end of the century.

Quantitative analysis of remote gas temperatures and concentrations from their infrared emission spectra

Techniques for obtaining quantitative values of the temperatures and concentrations of remote hot gaseous effluents from their measured passive emission spectra have been examined in laboratory experiments and on field trials. These emission spectra were obtained using an adapted FTIR spectrometer with 0.25 cm-1 spectral resolution. The CO2 and H2O vapour content in the plume from a 55 m smoke stack and the temperature of these gases were obtained by comparing the measured emission spectra with those modelled using the HITRAN atmospheric transmission database. The spatial distributions of CO2, CO and unburnt CH4 in a laboratory methane flame were reconstructed tomographically using a matrix inversion technique.

Adaptation of crops to climate change through genotypic responses to mean and extreme temperatures

The importance of temperature in the determination of the yield of an annual crop (groundnut; Arachis hypogaea L. in India) was assessed. Simulations from a regional climate model (PRECIS) were used with a crop model (GLAM) to examine crop growth under simulated current (1961-1990) and future (2071-2100) climates. Two processes were examined: the response of crop duration to mean temperature and the response of seed-set to extremes of temperature. The relative importance of, and interaction between, these two processes was examined for a number of genotypic characteristics, which were represented by using different values of crop model parameters derived from experiments. The impact of mean and extreme temperatures varied geographically, and depended upon the simulated genotypic properties. High temperature stress was not a major determinant of simulated yields in the current climate, but affected the mean and variability of yield under climate change in two regions which had contrasting statistics of daily maximum temperature. Changes in mean temperature had a similar impact on mean yield to that of high temperature stress in some locations and its effects were more widespread. Where the optimal temperature for development was exceeded, the resulting increase in duration in some simulations fully mitigated the negative impacts of extreme temperatures when sufficient water was available for the extended growing period. For some simulations the reduction in mean yield between the current and future climates was as large as 70%, indicating the importance of genotypic adaptation to changes in both means and extremes of temperature under climate change. (c) 2006 Elsevier B.V. All rights reserved.