Abstract
The spectral long-wave feedback parameter represents how Earth’s outgoing long-wave radiation adjusts to temperature changes and …Abstract
The spectral long-wave feedback parameter represents how Earth’s outgoing long-wave radiation adjusts to temperature changes and directly impacts Earth’s climate sensitivity. Most research so far has focused on the spectral integral of the feedback parameter. Spectrally resolving the feedback parameter permits inferring information about the vertical distribution of long-wave feedbacks, thus gaining a better understanding of the underlying processes. However, investigations of the spectral long-wave feedback parameter have so far been limited mostly to model studies. Here we show that it is possible to directly observe the global mean all-sky spectral long-wave feedback parameter using satellite observations of seasonal and interannual variability. We find that spectral bands subject to strong water-vapour absorption exhibit a substantial stabilizing net feedback. We demonstrate that part of this stabilizing feedback is caused by the change of relative humidity with warming, the radiative fingerprints of which can be directly observed. Therefore, our findings emphasize the importance of better understanding processes affecting the present distribution and future trends in relative humidity. This observational constraint on the spectral long-wave feedback parameter can be used to evaluate the representation of long-wave feedbacks in global climate models and to better constrain Earth’s climate sensitivity.more
The World Meteorological Organization (WMO) recommends that the most recent 30-year period, i.e., 1991–2020, be used to compute the climate normals of…The World Meteorological Organization (WMO) recommends that the most recent 30-year period, i.e., 1991–2020, be used to compute the climate normals of geophysical variables. A unique aspect of this recent 30-year period is that the satellite-based observations of many different essential climate variables are available during this period, thus opening up new possibilities to provide a robust, global basis for the 30-year reference period in order to allow climate-monitoring and climate change studies. Here, using the satellite-based climate data record of cloud and radiation properties, CLARA-A3, for the month of January between 1981 and 2020, we illustrate the difference between the climate normal, as defined by guidelines from WMO on calculations of 30 yr climate normals, and climatology. It is shown that this difference is strongly dependent on the climate variable in question. We discuss the impacts of the nature and availability of satellite observations, variable definition, retrieval algorithm and programmatic configuration. It is shown that the satellite-based climate data records show enormous promise in providing a climate normal for the recent 30-year period (1991–2020) globally. We finally argue that the holistic perspectives from the global satellite community should be increasingly considered while formulating the future WMO guidelines on computing climate normals.more
Scatterometer observations over land are sensitive to the water content in soil and vegetation, but have been rarely used to study seasonal changes in…Scatterometer observations over land are sensitive to the water content in soil and vegetation, but have been rarely used to study seasonal changes in the plant water status and seasonal development of deciduous trees. Here we use Advanced Scatterometer (ASCAT) observations to investigate the sensitivity of C-band backscatter to spring phenology of temperate deciduous broadleaf forests in Austria. ASCAT's multi-angle looking capability enables the observation of backscatter over a large range of incidence angles. The vegetation status affects the slope of the backscatter-incidence angle relationship. We discovered a maximum in the slope around the month April, hereafter referred to as spring peak, predominantly in regions covered by deciduous broadleaf forest. We hypothesized that the spring peak indicates the average timing of leaf emergence in the deciduous trees in the sensor footprint. The hypothesis was tested by comparing the timing of the spring peak to leaf unfolding observations from the PEP725 phenology database, to the increase of leaf area index (LAI) during spring, and to temperature. Our results demonstrate a good agreement between the ASCAT spring peaks, phenology observations and temperature conditions. The steepest increase in LAI however lags behind the ASCAT peak by several days to a few weeks, suggesting that the spring peak in fact marks the timing of maximum woody water content, which occurs right before leaf emergence. Based on these observations, we conclude that the ASCAT signal has a high sensitivity to spring reactivation and in particular water uptake of bare deciduous broadleaf trees. Our findings might provide the basis for novel developments to estimate eco-physiological changes of forests during spring at large scales.more
Antarctic sea ice is mostly seasonal. While changes in sea ice seasonality have been observed in recent decades, the lack of process understanding rem…Antarctic sea ice is mostly seasonal. While changes in sea ice seasonality have been observed in recent decades, the lack of process understanding remains a key challenge to interpret these changes. To address this knowledge gap, we investigate the processes driving the ice season onset, known as sea ice advance, using remote sensing and in situ observations. Here, we find that seawater freezing predominantly drives advance in the inner seasonal ice zone. By contrast, in an outer band a few degrees wide, advance is due to the import of drifting ice into warmer waters. We show that advance dates are strongly related to the heat stored in the summer ocean mixed layer. This heat is controlled by the timing of sea ice retreat, explaining the tight link between retreat and advance dates. Such a thermodynamic linkage strongly constrains the climatology and interannual variations, albeit with less influence on the latter.more