How robust are observed and simulated precipitation responses to tropical ocean warming?

Robust responses and links between the tropical energy and water cycles are investigated using multiple datasets and climate models over the period 1979-2006. Atmospheric moisture and net radiative cooling provide powerful constraints upon future changes in precipitation. While moisture amount is robustly linked with surface temperature, the response of atmospheric net radiative cooling, derived from satellite data, is less coherent. Precipitation trends and relationships with surface temperature are highly sensitive to the data product and the time-period considered. Data from the Special Sensor Microwave Imager (SSM/I) produces the strongest trends in precipitation and response to warming of all the datasets considered. The tendency for moist regions to become wetter while dry regions become drier in response to warming is captured by both observations and models. Citation: John, V. O., R. P. Allan, and B. J. Soden (2009), How robust are observed and simulated precipitation responses to tropical ocean warming?

Variability in clear-sky longwave radiative cooling of the atmosphere

The longwave radiative cooling of the clear-sky atmosphere (Q(LWc)) is a crucial component of the global hydrological cycle and is composed of the clear-sky outgoing longwave radiation to space (OLRc) and the net downward minus upward clear-sky longwave radiation to the surface (SNLc). Estimates of QLWc from reanalyses and observations are presented for the period 1979-2004. Compared to other reanalyses data sets, the European Centre for Medium-range Weather Forecasts 40-year reanalysis (ERA40) produces the largest Q(LWc) over the tropical oceans (217 W m(-2)), explained by the least negative SNLc. On the basis of comparisons with data derived from satellite measurements, ERA40 provides the most realistic QLWc climatology over the tropical oceans but exhibits a spurious interannual variability for column integrated water vapor (CWV) and SNLc. Interannual monthly anomalies of QLWc are broadly consistent between data sets with large increases during the warm El Nino events. Since relative humidity ( RH) errors applying throughout the troposphere result in compensating effects on the cooling to space and to the surface, they exert only a marginal effect on QLWc. An observed increase in CWV with surface temperature of 3 kg m(-2) K-1 over the tropical oceans is important in explaining a positive relationship between QLWc and surface temperature, in particular over ascending regimes; over tropical ocean descending regions this relationship ranges from 3.6 to 4.6 +/- 0.4 W m(-2) K-1 for the data sets considered, consistent with idealized sensitivity tests in which tropospheric warming is applied and RH is held constant and implying an increase in precipitation with warming.

Detection of flood extent in urban areas using high resolution TerraSAR-X data

Flooding is a major hazard in both rural and urban areas worldwide, but it is in urban areas that the impacts are most severe. An investigation of the ability of high resolution TerraSAR-X data to detect flooded regions in urban areas is described. An important application for this would be the calibration and validation of the flood extent predicted by an urban flood inundation model. To date, research on such models has been hampered by lack of suitable distributed validation data. The study uses a 3m resolution TerraSAR-X image of a 1-in-150 year flood near Tewkesbury, UK, in 2007, for which contemporaneous aerial photography exists for validation. The DLR SETES SAR simulator was used in conjunction with airborne LiDAR data to estimate regions of the TerraSAR-X image in which water would not be visible due to radar shadow or layover caused by buildings and taller vegetation, and these regions were masked out in the flood detection process. A semi-automatic algorithm for the detection of floodwater was developed, based on a hybrid approach. Flooding in rural areas adjacent to the urban areas was detected using an active contour model (snake) region-growing algorithm seeded using the un-flooded river channel network, which was applied to the TerraSAR-X image fused with the LiDAR DTM to ensure the smooth variation of heights along the reach. A simpler region-growing approach was used in the urban areas, which was initialized using knowledge of the flood waterline in the rural areas. Seed pixels having low backscatter were identified in the urban areas using supervised classification based on training areas for water taken from the rural flood, and non-water taken from the higher urban areas. Seed pixels were required to have heights less than a spatially-varying height threshold determined from nearby rural waterline heights. Seed pixels were clustered into urban flood regions based on their close proximity, rather than requiring that all pixels in the region should have low backscatter. This approach was taken because it appeared that urban water backscatter values were corrupted in some pixels, perhaps due to contributions from side-lobes of strong reflectors nearby. The TerraSAR-X urban flood extent was validated using the flood extent visible in the aerial photos. It turned out that 76% of the urban water pixels visible to TerraSAR-X were correctly detected, with an associated false positive rate of 25%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 58% and 19% respectively. These findings indicate that TerraSAR-X is capable of providing useful data for the calibration and validation of urban flood inundation models.

A simple model of convection with memory

There are at least three distinct time scales that are relevant for the evolution of atmospheric convection. These are the time scale of the forcing mechanism, the time scale governing the response to a steady forcing, and the time scale of the response to variations in the forcing. The last of these, tmem, is associated with convective life cycles, which provide an element of memory in the system. A highly simplified model of convection is introduced, which allows for investigation of the character of convection as a function of the three time scales. For short tmem, the convective response is strongly tied to the forcing as in conventional equilibrium parameterization. For long tmem, the convection responds only to the slowly evolving component of forcing, and any fluctuations in the forcing are essentially suppressed. At intermediate tmem, convection becomes less predictable: conventional equilibrium closure breaks down and current levels of convection modify the subsequent response.

Estimating surface CO2 fluxes from space-borne dry air mole fraction observations using an Ensemble Kalman filter

We have developed an ensemble Kalman Filter (EnKF) to estimate 8-day regional surface fluxes of CO2 from space-borne CO2 dry-air mole fraction observations (XCO2) and evaluate the approach using a series of synthetic experiments, in preparation for data from the NASA Orbiting Carbon Observatory (OCO). The 32-day duty cycle of OCO alternates every 16 days between nadir and glint measurements of backscattered solar radiation at short-wave infrared wavelengths. The EnKF uses an ensemble of states to represent the error covariances to estimate 8-day CO2 surface fluxes over 144 geographical regions. We use a 12×8-day lag window, recognising that XCO2 measurements include surface flux information from prior time windows. The observation operator that relates surface CO2 fluxes to atmospheric distributions of XCO2 includes: a) the GEOS-Chem transport model that relates surface fluxes to global 3-D distributions of CO2 concentrations, which are sampled at the time and location of OCO measurements that are cloud-free and have aerosol optical depths <0.3; and b) scene-dependent averaging kernels that relate the CO2 profiles to XCO2, accounting for differences between nadir and glint measurements, and the associated scene-dependent observation errors. We show that OCO XCO2 measurements significantly reduce the uncertainties of surface CO2 flux estimates. Glint measurements are generally better at constraining ocean CO2 flux estimates. Nadir XCO2 measurements over the terrestrial tropics are sparse throughout the year because of either clouds or smoke. Glint measurements provide the most effective constraint for estimating tropical terrestrial CO2 fluxes by accurately sampling fresh continental outflow over neighbouring oceans. We also present results from sensitivity experiments that investigate how flux estimates change with 1) bias and unbiased errors, 2) alternative duty cycles, 3) measurement density and correlations, 4) the spatial resolution of estimated flux estimates, and 5) reducing the length of the lag window and the size of the ensemble. At the revision stage of this manuscript, the OCO instrument failed to reach its orbit after it was launched on 24 February 2009. The EnKF formulation presented here is also applicable to GOSAT measurements of CO2 and CH4.

Does the North Atlantic Oscillation show unusual persistence on intraseasonal timescales?

Previous studies have argued that the autocorrelation of the winter North Atlantic Oscillation (NAO) index provides evidence of unusually persistent intraseasonal dynamics. We demonstrate that the autocorrelation on intraseasonal time-scales of 10–30 days is sensitive to the presence of interannual variability, part of which arises from the sampling of intraseasonal variability and the remainder of which we consider to be “externally forced”. Modelling the intraseasonal variability of the NAO as a red noise process we estimate, for winter, ~70% of the interannual variability is externally forced, whereas for summer sampling accounts for almost all of the interannual variability. Correcting for the externally forced interannual variability has a major impact on the autocorrelation function for winter. When externally forced interannual variability is taken into account the intrinsic persistence of the NAO is very similar in summer and winter (~5 days). This finding has implications for understanding the dynamics of the NAO.

A study of the sensitivity of ocean overturning circulation and climate to freshwater input in different regions of the North Atlantic

The Atlantic meridional overturning circulation (AMOC) is an important component of the climate system. Models indicate that the AMOC can be perturbed by freshwater forcing in the North Atlantic. Using an ocean-atmosphere general circulation model, we investigate the dependence of such a perturbation of the AMOC, and the consequent climate change, on the region of freshwater forcing. A wide range of changes in AMOC strength is found after 100 years of freshwater forcing. The largest changes in AMOC strength occur when the regions of deepwater formation in the model are forced directly, although reductions in deepwater formation in one area may be compensated by enhanced formation elsewhere. North Atlantic average surface air temperatures correlate linearly with the AMOC decline, but warming may occur in localised regions, notably over Greenland and where deepwater formation is enhanced. This brings into question the representativeness of temperature changes inferred from Greenland ice-core records.

Simulation of the Earth's radiation budget by the European Centre for Medium-Range Weather Forecasts 40-year reanalysis (ERA40)

The radiation budget simulated by the European Centre for Medium-Range Weather Forecasts (ECMWF) 40-year reanalysis (ERA40) is evaluated for the period 1979–2001 using independent satellite data and additional model data. This provides information on the quality of the radiation products and indirect evaluation of other aspects of the climate produced by ERA40. The climatology of clear-sky outgoing longwave radiation (OLR) is well captured by ERA40. Underestimations of about 10 W m−2 in clear-sky OLR over tropical convective regions by ERA40 compared to satellite data are substantially reduced when the satellite sampling is taken into account. The climatology of column-integrated water vapor is well simulated by ERA40 compared to satellite data over the ocean, indicating that the simulation of downward clear-sky longwave fluxes at the surface is likely to be good. Clear-sky absorbed solar radiation (ASR) and clear-sky OLR are overestimated by ERA40 over north Africa and high-latitude land regions. The observed interannual changes in low-latitude means are not well reproduced. Using ERA40 to analyze trends and climate feedbacks globally is therefore not recommended. The all-sky radiation budget is poorly simulated by ERA40. OLR is overestimated by around 10 W m−2 over much of the globe. ASR is underestimated by around 30 W m−2 over tropical ocean regions. Away from marine stratocumulus regions, where cloud fraction is underestimated by ERA40, the poor radiation simulation by ERA40 appears to be related to inaccurate radiative properties of cloud rather than inaccurate cloud distributions.

Inconsistencies between satellite estimates of longwave cloud forcing and dynamical fields from reanalyses

The greenhouse effect of cloud may be quantified as the difference between outgoing longwave radiation (OLR) and its clear-sky component (OLRc). Clear-sky measurements from satellite preferentially sample drier, more stable conditions relative to the monthly-mean state. The resulting observational bias is evident when OLRc is stratified by vertical motion; differences to climate model OLRc of 15 Wm−2 occur over warm regions of strong ascent. Using data from the ECMWF 40-year reanalysis, an estimate of cloud longwave radiative effect is made which is directly comparable with standard climate model diagnostics. The impact of this methodology on the cancellation of cloud longwave and shortwave radiative forcing in the tropics is estimated.

Analysis of moisture variability in the European Centre for Medium-Range Weather Forecasts 15-year reanalysis over the tropical oceans

We compare European Centre for Medium-Range Weather Forecasts 15-year reanalysis (ERA-15) moisture over the tropical oceans with satellite observations and the U.S. National Centers for Environmental Prediction (NCEP) National Center for Atmospheric Research 40-year reanalysis. When systematic differences in moisture between the observational and reanalysis data sets are removed, the NCEP data show excellent agreement with the observations while the ERA-15 variability exhibits remarkable differences. By forcing agreement between ERA-15 column water vapor and the observations, where available, by scaling the entire moisture column accordingly, the height-dependent moisture variability remains unchanged for all but the 550–850 hPa layer, where the moisture variability reduces significantly. Thus the excess variation of column moisture in ERA-15 appears to originate in this layer. The moisture variability provided by ERA-15 is not deemed of sufficient quality for use in the validation of climate models.

Can desert dust explain the outgoing longwave radiation anomaly over the Sahara during July 2003?

Measurements of the top‐of‐the‐atmosphere outgoing longwave radiation (OLR) for July 2003 from Meteosat‐7 are used to assess the performance of the numerical weather prediction version of the Met Office Unified Model. A significant difference is found over desert regions of northern Africa where the model emits too much OLR by up to 35 Wm−2 in the monthly mean. By cloud‐screening the data we find an error of up to 50 Wm−2 associated with cloud‐free areas, which suggests an error in the model surface temperature, surface emissivity, or atmospheric transmission. By building up a physical model of the radiative properties of mineral dust based on in situ, and surface‐based and satellite remote sensing observations we show that the most plausible explanation for the discrepancy in OLR is due to the neglect of mineral dust in the model. The calculations suggest that mineral dust can exert a longwave radiative forcing by as much as 50 Wm−2 in the monthly mean for 1200 UTC in cloud‐free regions, which accounts for the discrepancy between the model and the Meteosat‐7 observations. This suggests that inclusion of the radiative effects of mineral dust will lead to a significant improvement in the radiation balance of numerical weather prediction models with subsequent improvements in performance.