Climate Change Observations of Indigenous Communities in the Indian Himalaya

Mountains are important global sites for monitoring biological and socioecological responses to climate change, and the Himalaya has some of the world’s most rapid and visible signs of climate change. The increased frequency and severity of climate anomalies in the region are expected to significantly affect livelihoods of indigenous communities in the region. This study documents the perceptions of indigenous communities of climate change in the western Himalaya of India. The study highlights the power of knowledge and understanding available to indigenous people as they observe and respond to climate change impacts. We conducted a field-based study in 14 villages that represent diverse socioecological features along an altitudinal range of 1000–3800 m MSL in the western Himalaya. Among the sampled population, most of the respondents (>95%) agreed that climate is changing. However, people residing at low- and high-altitude villages differ significantly in their perception, with more people at high altitudes believing in an overall warming trend. Instrumental temperature and rainfall from nearby meteorological stations also supported the perception of local inhabitants. The climate change perceptions in the region were largely determined by sociodemographic variables such as age, gender, and income as well as altitude. A logistic regression, which exhibited significant association of sociodemographic characteristics with climate change perceptions, further supported these findings. The study concluded that the climate change observations of local communities can be usefully utilized to develop adaptation strategies and mitigation planning in the Himalayan region.

Cryogenic cave carbonate formation during the Industrial Era in the Central Pyrenees (Iberian Peninsula)

<p>Cryogenic cave carbonates (CCC) are rare speleothems that form when water freezes inside cave ice bodies. CCC have been used as an proxy for permafrost degradation, permafrost thickness, or subsurface ice formation. The presence of these minerals is usually attributed to warm periods of permafrost degradation. We found coarse crystalline CCC types within transparent, massive congelation ice in two Pyrenean ice caves in the Monte Perido Massif: Devaux, located on the north face at 2828 m a.s.l., and Sarrios 6, located in the south face at 2780 m a.s.l. The external mean annual air temperature (MAAT) at Devaux is ~ 0°C, while at Sarrios 6 is ~ 2.5°C. In the Monte Perdido massif discontinuous permafrost is currently present between 2750 and 2900 m a.s.l. and is more frequent above 2900 m a.s.l. in northern faces. In Devaux, air and rock temperatures, as well as the presence of hoarfrost and the absence of drip sites indicate a frozen host rock. Moreover, a river flows along the main gallery, and during winters the water freezes at the spring causing backflooding in the cave. In contrast, Sarrios 6 has several drip sites, although the gallery where CCC were collected is hydrologically inactive. This gallery opened in recent years due to ice retreat. During spring, water is present in the gallery due to the overflow of ponds forming beneath drips. CCC commonly formed as sub-millimeter-size spherulites, rhombohedrons and rafts. <sup>230</sup>Th ages of the same CCC morphotype indicate that their formation took place at 1953±7, 1959±14, 1957±14, 1958±15, 1974±16 CE in Devaux, while in Sarrios 6 they formed at 1964±5, 1992±2, 1996±1 CE. The cumulative probability density function indicates that the most probable formation occurred 1957-1965 and 1992-1997. The instrumental temperature record at 2860 m a.s.l. indicates positive MAAT in 1964 (0.2°C) and 1997 (0.8°C). CCC formation could thus correspond with those two anomalously warm years. The massive and transparent ice would indicate a sudden ingress of water and subsequent slow freezing inside both caves during those years. Probably, CCC formation took place at a seasonal scale during the annual cycle.</p>

Identifying exposure biases in early instrumental data

<p>Long observational records of land surface air temperature are vital to our understanding of climate variability and change, as well as for testing predictions of climatic trends. However, of the relatively few long observational records which exist, many contain inhomogeneities or biases resulting from changing instrumentation, station location/surroundings and/or observing practises. One of the most significant issues is the exposure bias. Prior to the widespread adoption of louvered Stevenson-type screens in the late-19<sup>th</sup> century, various (often insufficient) approaches were used to shield thermometers. Each approach exposed the thermometer to differing levels of solar radiation, thus introducing inhomogeneities into individual station records and biases across regions, if similar approaches were used. Poorly shielded thermometers, for example, tended to read higher during the summer half year than those in Stevenson-type screens. Despite a number of studies documenting the presence of the exposure bias in early instrumental data, relatively few corrections have been applied or incorporated into global temperature datasets. This is largely due to the pervasive nature of the bias and a lack of observational metadata impeding bias identification or estimation of the appropriate correction.</p><p>In this work we explore a range of datasets to identify the potential for exposure bias in early instrumental data. We analyse historical data, corrections applied to homogenized datasets, as well as the small number of parallel measurements from differentially-shielded thermometers, in order to better define the characteristics of the exposure bias. These characteristics are then used to identify potential instances of exposure bias in early instrumental temperature records. We consider differences in seasonal anomalies, which is a key feature of many exposure biases, as well as their geographical variation (focussing mostly, but not solely, on Europe). We analyse how these behave at stations where it is known that exposure bias has already been adjusted for (though perhaps not completely) versus those that have not been. We also make comparisons with proxy reconstructions of temperature as an independent reference that is not susceptible to the same biases as the early instrumental data.</p><p>This work forms part of the NERC-funded GloSAT project which is developing a global surface air temperature dataset starting in 1781. The ultimate aim of the work reported here is to refine the error associated with these biases, in order to improve the representation of the exposure bias in error models used for gridded instrumental temperature datasets.</p>

Depth and seasonal biases in organic temperature proxies: a modelling study

<p>For more than a decade TEX<sub>86</sub> and U<sup>K’</sup><sub>37</sub>, derived from ratios of biomarker lipids have widely been used as organic paleotemperature proxies. Yet, these proxies, especially TEX<sub>86</sub>, have several uncertainties associated with factors such as depth and seasonal biases which are complicating its application as an annual mean sea-surface temperature (SST) proxy. To constrain this impact, we performed a relatively simple modelling exercise where we use instrumental temperature and nutrient data from 40 locations across the globe to predict theoretical proxy values and compare them with measured core-top proxy values.</p><p>The model first uses instrumental nutrient and temperature data, and probability density functions to predict the theoretical depth occurrence of the source organisms of the two proxies. Additionally, seasonal bias was introduced by predicting seasonal occurrences using instrumental nutrient and chlorophyll data. This was used to calculate the depth- and season weighed temperature signal annually deposited in the sediment, which in turn was converted to theoretical proxy values using culture or mesocosm calibrations. This showed, as expected, that depth and seasonal biases introduced scatter in the correlation between theoretical proxy values and annual mean SST but still highly significant for both U<sup>K’</sup><sub>37</sub> (r<sup>2</sup>= 0.96), and TEX<sub>86</sub> (r<sup>2</sup>= 0.77). We find that the theoretical proxy values are much lower than measured proxy value for TEX<sub>86</sub>, which tentatively suggests that TEX<sub>86 </sub>might in fact be coming from shallower depths or that the mesocosm calibration is incorrect. Our model for U<sup>K’</sup><sub>37</sub> results in theoretical values similar to measured values except for low temperature locations. This might suggest an influence of seasonal bias towards more warmer summer seasons which is more pronounced in high latitudes than in tropics.</p>

On the role of natural multidecadal oscillations on global warming and its hiatus

In this study, we investigate the role of the multidecadal oscillation patterns in the global temperature in the global warming hiatus. We analyze the global instrumental temperature records and multiple tree-ring temperature reconstruction records using wavelet transforms and register the presence of a multidecadal cycle of approximately 55-75 years. The hiatus and post-hiatus rise in temperature arises from the declining phase of the multidecadal oscillation which temporally compensates the rising phase. The unusual rise in the temperature after the hiatus is possibly explained by the positive uprising phase of this natural cycle. The origin of the global warming debate has been partly ascribed to faulty calculations or biased judgments. However, in these studies, little emphasis has been given to the possible presence of multidecadal oscillation patterns in the global temperature, which may lead to such an effect. Our result demonstrates that, phase of this cycle has accidentally played an important role in fueling the global warming debate. Therefore, while assessing any future climate changes, such possibilities should be accounted.

Global Ensemble of Temperatures over 1850–2018: Quantification of Uncertainties in Observations, Coverage, and Spatial modelling (GETQUOCS)

Instrumental temperature records are derived from the network of in situ measurements of land and sea surface temperatures. This observational evidence is seen as fundamental to climate science. Therefore, the accuracy of these measurements is of prime importance for the analysis of temperature variability. There are spatial gaps in the distribution of instrumental temperature measurements across the globe. This lack of spatial coverage introduces coverage error. An approximate Bayesian computation based multi-resolution lattice kriging is developed and used to quantify the coverage errors through the variance of the spatial process at multiple spatial scales. It critically accounts for the variation in the parameters of this advanced spatial statistics model itself, thereby providing for the first time a full description of both the spatial coverage uncertainties along with the uncertainties in the modeling of these spatial gaps. These coverage errors are combined with the existing estimates of uncertainties due to observational issues at each station location. It results in an ensemble of 100,000 monthly temperatures fields over the entire globe that samples the combination of coverage, parametric and observational uncertainties from 1850 till 2018 over a 5° × 5° grid.

Emergent Scale Invariance and Climate Sensitivity

Earth's global surface temperature shows variability on an extended range of temporal scales and satisfies an emergent scaling symmetry. Recent studies indicate that scale invariance is not only a feature of the observed temperature fluctuations, but an inherent property of the temperature response to radiative forcing, and a principle that links the fast and slow climate responses. It provides a bridge between the decadal- and centennial-scale fluctuations in the instrumental temperature record, and the millennial-scale equilibration following perturbations in the radiative balance. In particular, the emergent scale invariance makes it possible to infer equilibrium climate sensitivity (ECS) from the observed relation between radiative forcing and global temperature in the instrumental era. This is verified in ensembles of Earth system models (ESMs), where the inferred values of ECS correlate strongly to estimates from idealized model runs. For the range of forcing data explored in this paper, the method gives best estimates of ECS between 2.3 and 3.4 K.

Sensitivity study of the instrumental temperature corrections on Brewer total ozone column measurements

The instrumental temperature corrections to be applied to the ozone measurements by the Brewer spectrophotometers are derived from the irradiance measurements of internal halogen lamps in the instruments. These characterizations of the Brewer spectrophotometers can be carried out within a thermal chamber, varying the temperature from −5 to +45 ∘C, or during field measurements, making use of the natural change in ambient temperature. However, the internal light source used to determine the thermal sensitivity of the instrument could be affected in both methods by the temperature variations as well, which may affect the determination of the temperature coefficients. In order to validate the standard procedures for determining Brewer's temperature coefficients, two independent experiments using both external light sources and the internal halogen lamps have been performed within the ATMOZ Project. The results clearly show that the traditional methodology based on the internal halogen lamps is not sensitive to the temperature-caused changes in the spectrum of the internal light source. The three methodologies yielded equivalents results, with differences in total ozone column below 0.08 % for a mean diurnal temperature variation of 10 ∘C.

Phase Changes and Seasonal Warming in Early Instrumental Temperature Records

Phase analyses of the annual cycle of monthly temperature time series that date back to the eighteenth century show trending behavior that has been difficult to interpret. Negative trends in the estimated phase have been identified with precession of Earth’s axis of rotation, but the implied later onset of seasons is at odds with recent satellite measurements and with the phenological record. Positive trends in the phase and the occurrence of trends of both signs in temperature time series from geographically nearby locations have remained mysterious. This paper shows that there is a mathematical equivalence between trends in phases and seasonally differing warming trends, in particular more intense warming in winters than in summers. Using temperature time series from 16 Northern Hemispheric locations reaching back to the eighteenth century and a statistical model that can estimate the seasonal warming trends, the authors reject the hypothesis that the timing of the seasons in these locations is jointly driven by precession.