Total Cloud Research Articles

전운량을 고려한 정찰위성 작전효과 분석 방법론 연구: ① 북한지역 전운량 빅데이터 분석을 통한 취약요인 분석

전운량을 고려한 정찰위성 작전효과 분석 방법론 연구: ① 북한지역 전운량 빅데이터 분석을 통한 취약요인 분석

전운량을 고려한 정찰위성 작전효과 분석 방법론 연구: ② 위성관측 취약요인에 기반한 정찰위성 작전효과 분석

전운량을 고려한 정찰위성 작전효과 분석 방법론 연구: ② 위성관측 취약요인에 기반한 정찰위성 작전효과 분석

Spatial Distributions of Cloud Occurrences in Terms of Volume Fraction as Inferred from CloudSat and CALIPSO

The cloud amount, referred to as the frequency of cloud occurrences, is of great importance for the Earth–atmosphere system. It was conventionally quantified as the area fraction of clouds in a given region, discarding the three-dimensional nature of both cloud entities and their spatial distribution. Although the area fraction is explicit, it is the volume fraction that fully depicts cloud occurrences, and the area fraction is just related to a projection of the volume fraction. In this study, by using spaceborne radar measurements, the spatial distribution of cloud volume fraction throughout the troposphere was investigated, and the contributions of various cloud types at each location were clarified. Overall, the volume fraction of total clouds in the whole troposphere is 15.9%, while the corresponding area fraction relative to the global surface is 73.6%. The peak volume fraction occurs at 1 km altitude, mainly contributed by stratocumulus and cumulus. For a single cloud type, the maximum fraction is 48.8%, which is from stratocumulus and occurs at 1 km altitude above the Greenland Sea. Half of the eight cloud types, altostratus, cirrus, nimbostratus, and deep convective clouds, reach the nominal tropopause. In particular, the vertical distribution difference among multiple cloud types in each category (low-level, middle-level, and vertically extending) was clarified, and it was found that the dominant cloud type in a category varies notably with the location in the atmosphere.

Long-Term Trends of Astroclimatic Parameters above the Terskol Observatory

Astroclimatic conditions characterize the quality of an astronomical site. The Terskol Observatory was founded over 42 years ago in 1980. The astronomical site (coordinates 43°16′29″ N, 42°30′03″ E) is located about 10 km from Mt. Elbrus in the northern Caucasus Mountains. The paper presents the results of an analysis of long-term variations from 1980 to 2022 of astroclimatic parameters such as total cloud cover, precipitable water vapor, and wind speed at a level of 200 hPa above the Terskol Observatory using atmospheric ERA5 Reanalysis data from the European Center for Medium-Range Weather Forecast. The probability distributions and seasonal variations of the astroclimatic parameters are also presented. Long-term trends of the astroclimatic parameters are studied with statistically significant trend analysis methods using the Mann–Kendall test and the Sen’s slope test to estimate the magnitude of the changes. The results show non-significant decreases of annual average 200-hPa wind speed and increases in precipitable water vapor, but significant (99 per cent confidence level) long-term decreasing of total cloud cover above the Terskol Observatory.

An hourly solar radiation prediction model using eXtreme gradient boosting algorithm with the effect of fog-haze

Hourly global solar radiation data is an important factor for solar energy utilization. Due to the lack of solar radiation observation stations in many areas, some hourly solar radiation models are proposed to predict hourly solar radiation. However, the existing models perform poorly in heavy fog-haze areas because the weakening effect of fog-haze on solar radiation is not considered. Thus, in this paper, hourly global solar radiation prediction models are developed considering air quality index (AQI) using XGBoost algorithm. The results show a general improvement in the accuracy of models with AQI as an additional input (Model B1-B6) compared to models that do not consider AQI (Model A1-A6). Compared to Model A, Model B have an increase in R value from 0.927 to 0.948, a decrease in RMSE value from 0.300 to 0.282 and a decrease in MAPE value from 0.159 to 0.145. In addition, for hourly solar radiation prediction, the six most important inputs are the day of the year, air temperature difference, surface temperature difference, hour, AQI, and total cloud cover.

Mechanical and Thermal Forcings of Asian Large-Scale Orography on Spring Cloud Amount and Atmospheric Radiation Budget over East Asia

Abstract Asian large-scale orography profoundly influences circulation in the North Hemisphere. Considerable spring top-of-the-atmosphere (TOA) radiative cooling over Southeast China (SEC) is very likely related to upstream orography forcing. Here we investigate the mechanical and thermal forcings of Asian large-scale orography, particularly the Tibetan Plateau (TP), on downstream East Asian cloud amount and atmospheric radiation budget during March–April using the Global Monsoons Model Intercomparison Project simulations. The thermal forcing drives significant surface heating and a low-level cyclone over the TP, pumping low-level air to the middle troposphere. Ascent and water vapor convergence triggered by the thermal forcing favor air condensation, low–middle clouds, and resultant strong spring cloud radiative cooling over SEC. Moreover, the thermal forcing moves the position of cloud radiative cooling westward toward the TP. The TP’s blocking role weakens low-level westerlies over SEC, but its deflecting role increases downstream high-level westerlies, dynamically favoring cloud formation over SEC and the eastward ocean. In addition, the TP can force ascent and increase cloud amounts over the western and central TP. The thermal forcing contributes to 57.1% of total cloud amount and 47.6% of TOA cloud radiative cooling induced by the combined orography forcing over SEC while the mechanical one accounts for 79.4% and 95.8% of the counterparts over the ocean to the east of SEC. Our results indicate that Asian large-scale orography shapes the contemporary geographical distribution of spring East Asian cloud amount and atmospheric radiation budget to a large extent. Significance Statement Clouds tied to large-scale topography and circulation exhibit some remarkable geographical distributions. The global strongest cloud radiative cooling, with an intensity of up to −90 W m−2, occurs over Southeast China (SEC) during March–April. The primary purpose of this study is to understand the influences of Asian large-scale orography, particularly the Tibetan Plateau (TP), on this unique climatic phenomenon using the latest climate model simulations. Our results show that Asian large-scale orography forcing significantly increases ascent, low–middle cloud formation, and resultant strong spring cloud radiative cooling over SEC and downstream ocean. The sensible-heat-driven air pump induced by the TP’s thermal forcing maintains strong cloud radiative cooling over SEC. This study provides valuable insights that link Asian large-scale orography forcing to downstream cloud–radiation characteristics.

Decadal Stability and Trends in the Global Cloud Amount and Cloud Top Temperature in the Satellite-Based Climate Data Records

Forty years of cloud observations are available globally from satellites, allowing derivation of climate data records (CDRs) for climate change studies. The aim of this study is to investigate how stable these cloud CDRs are and whether they qualify stability requirements recommended by the WMO’s Global Climate Observing System (GCOS). We also investigate robust trends in global total cloud amount (CA) and cloud top temperature (CTT) that are significant and common across all CDRs. The latest versions of four global cloud CDRs, namely CLARA-A3, ESA Cloud CCI, PATMOS-x, and ISCCP-HGM are analysed. This assessment finds that all three AVHRR-based cloud CDRs (i.e., CLARA-A3, ESA Cloud CCI and PATMOS-x) satisfy even the strictest GCOS stability requirements for CA and CTT when averaged globally. While CLARA-A3 is most stable in global averages when tested against MODIS-Aqua, PATMOS-x offers the most stable CDR spatially. While we find these results highly encouraging, there remain, however, large spatial differences in the stability of and across the CDRs. All four CDRs continue to agree on the statistically significant decrease in global cloud amount over the last four decades, although this decrease is now weaker compared to the previous assessments. This decreasing trend has been stabilizing or even reversing in the last two decades; the latter is seen also in MODIS-Aqua and CALIPSO GEWEX datasets. Statistically significant trends in CTT are observed in global averages in the AVHRR-based CDRs, but the spatial agreement in the sign and the magnitude of the trends is weaker compared to those in CA. We also present maps of Common Stability Coverage and Common Trend Coverage that could provide a valuable metric to carry out an ensemble-based analysis of the CDRs.

An asymmetric relationship between Tibetan Plateau surface temperature regimes and oceanic–atmospheric circulations

AbstractAs a high‐altitude region, the Tibetan Plateau (TP) is sensitive to climate change. Since the 1960s, the TP has experienced significant spatial‐variant warming, vital to changing the region's terrestrial ecosystem. To understand surface air temperature (SAT) regimes over the TP, we investigated their link with teleconnections using observational and reanalysis datasets from 1982 to 2019. We employed wavelet analysis, empirical orthogonal teleconnection (EOT), partial regression, canonical correlation analysis and t test. Our results indicate an asymmetrical connection between teleconnections and SAT, with Atlantic Multidecadal Oscillation (AMO) predominant over the northern TP. In contrast, the El Niño–Southern Oscillation (ENSO) is more prevalent in the southern part. The spatial variance was potentially related to windspeed, total cloud cover (TCC), net longwave radiation (NLWR), net shortwave radiation (NSWR), cloud‐forcing net longwave flux (CF‐NLWF) and cloud‐forcing net shortwave flux (CF‐NLWF) anomalies. ENSO and Pacific Decadal Oscillation (PDO) modulate cloud cover variation in the southern TP, mainly the southwest, via the monsoon and subtropical westerlies. In the north, cloud cover variation is related to the moisture transported by the AMO‐induced prevailing westerlies. The study examined the complex interplay between teleconnections, SAT and cloud radiative forcing by examining the cloud cover and radiation balance relationship. These findings contribute to understanding climate change impacts on the TP, informing climate projections and guiding adaptation strategies by elucidating the relationship between TP temperature variation and oceanic–atmospheric oscillation patterns.

Early Humidity Measurements by Louis Morin in Paris between 1701 and 1711—Data and Metadata

This paper discusses what is, to our knowledge, the oldest subdaily measurement series of humidity taken over several years. Louis Morin performed the measurements in Paris, three times a day, between May 1701 and June 1711. A correlation analysis of Morin’s humidity measurements with various meteorological variables yields results comparable to those of a parallel analysis of the relative humidity measurements of the E-OBS data: the Spearman correlation coefficient between the humidity and the daily minimum temperature is −0.43 (p < 0.01); with the mean temperature, it is −0.54 (p < 0.01); with the maximum temperature, it is −0.59 (p < 0.01); with the diurnal temperature range, it is −0.65 (p < 0.01); and with the total cloud cover, 0.33 (p < 0.01). However, with a Spearman correlation coefficient of 0.11 (p < 0.01), no correlation is found with the precipitation data. Further evidence for the plausibility of the measurements is shown by a day-by-day analysis of the first half-year of 1709. Here, abrupt changes in the humidity measurements of Morin can be explained by the other measurements/observations of Morin. According to the correlation analysis, indirect notes in his journal, and others, we argue that Morin used the hygrometer developed by Vincenzo Viviani. However, the conversion of the data to common units is not performed and is subject to further research.

Examining cloud vertical structure and radiative effects from satellite retrievals and evaluation of CMIP6 scenarios

Abstract. Clouds exhibit a wide range of vertical morphologies that are regulated by distinct atmospheric dynamics and thermodynamics and are related to a diversity of microphysical properties and radiative effects. In this study, the new CERES-CloudSat-CALIPSO-MODIS (CCCM) RelD1 dataset is used to investigate the morphology and spatial distribution of different cloud vertical structure (CVS) types during 2007–2010. The combined active and passive satellites provide a more precise CVS than those only based on passive imagers or microwave radiometers. We group the clouds into 12 CVS classes based on how they are located or overlapping in three standard atmospheric layers with pressure thresholds of 440 and 680 hPa. For each of the 12 CVS types, the global average cloud radiative effects (CREs) at the top of the atmosphere, within the atmosphere and at the surface, as well as the cloud heating rate (CHR) profiles are examined. The observations are subsequently used to evaluate the variations in total, high-, middle- and low-level cloud fractions in CMIP6 models. The “historical” experiment during 1850–2014 and two scenarios (ssp245 and ssp585) during 2015–2100 are analyzed. The observational results show a substantial difference in the spatial pattern among different CVS types, with the greatest contrast between high and low clouds. Single-layer cloud fraction is almost 4 times larger on average than multi-layer cloud fraction, with significant geographic differences associated with clearly distinguishable regimes, showing that overlapping clouds are regionally confined. The global average CREs reveal that four types of CVSs warm the planet, while eight of them cool it. The longwave component drives the net CHR profile, and the CHR profiles of multi-layer clouds are more curved and intricate than those of single-layer clouds, resulting in complex thermal stratifications. According to the long-term analysis from CMIP6, the projected total cloud fraction decreases faster over land than over the ocean. The high clouds over the ocean increase significantly, but other types of clouds over land and the ocean continue to decrease, helping to offset the decrease in oceanic total cloud fraction. Moreover, it is concluded that the spatial pattern of CVS types may not be significantly altered by climate change, and only the cloud fraction is influenced. Our findings suggest that long-term observed CVS should be emphasized in the future to better understand CVS responses to anthropogenic forcing and climate change.

Sunshine duration and solar radiation contributed to severe Bell's palsy: An 11-year time series analysis based on a distributed lag non-linear model model.

Although previous studies have suggested that meteorological factors are associated with Bell's palsy, articles on this topic are rare and the results are inconsistent. We aim to reveal the relationship between exposure to different meteorological factors and the onset of severe Bell's palsy (SBP) with daily data. A case-crossover study based on time-series data was applied, and the minimum risk value of each climatic factor was set as the reference value. We fitted a distributed lag non-linear model (DLNM) which applied quasi-Poisson regression to evaluate the exposure-response association and the lag-response association of meteorological factors on the occurrence of SBP. The mode value and per-decile interval value of each meteorological factor were all included in the analysis. Sensitivity analyses were conducted to test the robustness of results. A total of 863 SBP patients (474 males and 389 females) from 7 hospitals in the Shenzhen Futian District were selected from January 2009 to February 2020. The highest relations effect was tested in the cumulative exposure-response result shown as follows; mean temperature at the minimum value 15.3°C with RR of 10.370 (1.557-69.077) over lag 0 to 13; relative humidity at the 30th value 71% with RR of 8.041 (1.016-63.616) over lag 0 to 14; wind speed at the 90th value 31 (0.1 m/s) with RR of 1.286 (1.038-1.593) over lag 0; mean air pressure at the 30th value 1001.4 (pa) with RR of 9.052 (1.039-78.858) over lag 0 to 5; visibility at the 80th value 26.5 (km) with RR of 1.961 (1.005-1.423) over lag 0 to 2; average total cloud cover at the max value 100 (%) with RR 1.787 (1.014-3.148) over lag 0 to 2; sunshine duration at the 10th value 0.1 (h) with RR of 4.772 (1.018-22.361); daily evaporation shows no relationship in the cumulative result; daily average solar radiation at the minimum value 0 (W/m2) with RR of 5.588 (1.184-26.382). There is a relationship between wind speed and the onset of SBP, while mean air pressure, visibility, and average total cloud cover, especially sunshine duration and solar radiation which showed a strong effect, may be associated with severe clinical symptoms of SBP. Mean temperature and relative humidity may affect the course of SBP.

Spatial–Temporal Variations in Temperature and Precipitation Extremes during 1960–2019 in Guizhou Province, China

Under the background of global warming, climate extremes have become a crucial issue with distinct heterogeneity features in different regions. Hence, spatial–temporal changes in temperature and precipitation extremes in Guizhou Province were investigated utilizing daily maximums and minimums of temperature and daily precipitation data during 1960–2019 based on trend analysis. It was concluded that, firstly, all warm extremes but warm spell duration indicator (WSDI) are significantly enhanced, whereas for cold extremes, the monthly minimum value of daily minimum temperature (TNn) is significantly enhanced, while cool nights (TN10P), frost days (FD0), ice days (ID0), and cold spell duration indicator (CSDI) are significantly decreased. And all precipitation extremes but consecutive wet days (CWD) have no significant variational trend in Guizhou Province. Secondly, variational trends of temperature extremes are more prominent and robust in western Guizhou Province. Temperature and precipitation extremes show large differences from spring to winter. Thirdly, temperature extremes are closely correlated with strength, area, and the westernmost ridge point index of western Pacific subtropical high (WPSH), whereas precipitation extremes show no distinct correlation with WPSH. The WPSH has significantly strengthened and shifted westward in the past 60 years, leading to less total cloud cover and more downward solar wave flux reaching Earth’s surface, accordingly, exacerbating warm extremes and weakening cold extremes. These results will benefit understanding the heterogeneity of climate extremes at a regional scale.

Diurnal Cycle Dependence of ENSO Influence on the Winter Surface Air Temperature in Southeastern China

Abstract It is well known that El Niño–Southern Oscillation (ENSO) can influence the East Asian winter climate by modifying the atmospheric circulation over the western North Pacific (WNP). While the impact on precipitation in southeastern China has been extensively studied, the ENSO signal in surface air temperature (SAT) remains overlooked. In this paper, we identify robust ENSO footprints in the winter daily minimum SAT in southeastern China, with El Niño winters generally accompanied by warmer-than-normal minimum SAT anomalies. In contrast, the responses of maximum SAT are weak and negligible, suggesting a diurnal cycle–dependent ENSO influence. Further analysis indicates that this diurnal cycle dependence stems primarily from the disparate surface radiative heating between day and night induced by ENSO-related local total cloud cover (TCC) change. The warmer minimum SAT occurring in the early morning of El Niño winters is mainly caused by the enhanced surface downward longwave radiative heating as a result of the TCC increase. However, in the afternoon of El Niño winters, although the anomalous horizontal advection of warm air plays a role, there is surface radiative cooling as the weakening of solar radiation due to TCC reflection overwhelms the increase in downward longwave radiation, which leads to a weakened sensible heat flux and thus has a cooling effect on the SAT. Ultimately, these two processes effectively cancel each other out and together produce insignificant maximum SAT responses. Our conclusions carry important implications for the seasonal to interannual winter climate prediction in southeastern China. Significance Statement The purpose of this study is to better understand how ENSO influences winter surface air temperature in southeastern China. Despite insignificant responses of winter daily maximum temperature to ENSO, we find here a robust ENSO influence on the daily minimum temperature, with warm anomalies tending to occur during El Niño events. Further evidence suggests that this diurnal cycle–dependent ENSO influence is mainly caused by ENSO-induced change in local cloudiness, which has a different radiative heating effect between day and night. Our findings are of great importance for improving regional climate prediction, which will benefit social and economic activities.

Accurately forecasting solar radiation distribution at both spatial and temporal dimensions simultaneously with fully-convolutional deep neural network model

Accurately forecasting solar radiation is of great significance to solar energy utilization. To forecast the spatial and temporal distributions of solar radiation simultaneously, a deep neural network model named MRE-UNet is proposed, the solar radiation data in Heilongjiang province is taken as an example to test the forecasting performance in different periods ahead forecasting cases. According to the evaluation results, an 16 h historical solar radiation data was determined to be the best choice for input, and the minimum of MSE can reach 6.47 × 10−4, 1.38 × 10−3 and 2.69 × 10−3 for 1 h, 3 h and 6 h ahead forecasting cases, respectively. The transferability of the MRE-UNet is tested by performing the solar radiation nowcasting in Hubei province, China using the pre-trained MRE-UNet trained by the solar radiation data in Heilongjiang province. The robustness of MRE-UNet is tested by monitoring the effects of adding different level of noise, and MSE keeps to be 6.27 × 10−4 even though the measuring noise increase to be 50%. For further demonstration on the effectiveness of MRE-UNet in spatiotemporal forecasting, the performance in total cloud cover forecasting is also tested, and satisfactory forecasting results are obtained. Finally, spatiotemporal correlation analysis on solar radiation and total cloud cover data is carried out, a potential reason for satisfying forecasting performance of MRE-UNet is given. From this work, MRE-UNet proposed can be provided as an efficient tool for dealing with further solar radiation spatiotemporal forecasting problem, and the spatiotemporal correlation characteristics can be employed as the basis for further developing effective solar radiation forecasting approach to a degree.

Spatial and Temporal Analysis of Climatic Precursors before Major Earthquakes in Iran (2011–2021)

The present study provides a systematic assessment of the relationships between climatic variables and major earthquakes (M > 6) in Iran (2011–2021). These variables include total cloud cover (tcc), low cloud cover (lcc), total precipitation (tp), surface latent heat flux (slhf), and total column rainwater (tcrw). Based on a wider set of variables provided by a multidimensional global dataset (ERA5), the combination of a cross-correlation function (CCF) and receiver operating characteristic (ROC) was used to develop the spatial and temporal analytic relations. Covering maximal values from 0.42 to 0.92, the CCF plots revealed that an increase in climatic parameters could provide valuable information about impending earthquake activity within 8 to 20 days. The mean values of tcc, lcc, tp, slhf, and tcrw were found to increase by 95%, 60%, 80.0 mm, 105 W/m2, and 95 kg−3/m2, respectively. In fact, with the mean AUC (area under the curve) indices ranging from 0.677 (tcc) to 0.810 (tcrw) prior to major earthquakes, the ROC plots allowed for discrimination between seismic and climatic variables ranging from “acceptable” to “excellent”. The changes in the climatic variables under study were due to anomalous air ionization and water condensation in the atmosphere, which can be regarded as short-term precursors to major earthquakes.

Prediction and influencing factors of photovoltaic system power generation of a single house based on continuously measured data

With the development of photovoltaic (PV) power generation systems in single houses, research has recently focused on the prediction of PV power generation to match PV power generation with building energy consumption characteristics. However, prediction models for PV power generation under different weather conditions based on the actual monitoring data of the PV power generation system in a single house are still lacking. The present study is based on the actual monitoring of PV power generation data of a single house with a PV system that was installed in Beijing 5 years ago. We analysed the main weather factors affecting PV power generation and power conversion efficiency (PCE). The results showed a positive correlation between power generation and solar radiation, with the ambient temperature (Ta) and total cloud cover (TCC) being the main weather factors affecting power generation and PCE. Based on the analysis results, a support vector regression (SVR) model was established to predict PV power generation. In addition, the mean absolute error (MAE), mean absolute percentage error (MAPE) and coefficient of variation (R2) of the SVR model were 3.39, 34.7% and 0.86, respectively, which can accurately be used to predict PV power generation under different weather types.

Improving the blend of multiple weather forecast sources by Reliability Calibration

AbstractCreating a forecast that is seamless across time yet is optimal at each forecast validity time is often achieved by blending forecasts from multiple Numerical Weather Prediction models (or using other forecast sources, such as an extrapolation nowcast). With the increasing usage of convection‐permitting ensemble models at shorter lead times, the blending of these forecasts with longer‐range ensemble models with parameterized convection can lead to a clear transition from one forecast source to another. This is particularly noticeable when visualizing the evolution of the gridded forecast. Calibrating the forecast sources with a common truth prior to blending provides a method of improving forecast skill whilst also unifying the characteristics of the forecasts to create a smoother blend throughout the evolution of the forecast. In this work, a non‐parametric method for calibrating the reliability of the forecast without degrading the forecast resolution is assessed for its usability for gridded precipitation rate and total cloud amount forecasts. Reliability is markedly improved resulting in a similar skill between forecast sources during the blending period. Further refinements to the technique removed artefacts in the gridded forecasts. Caveats, including a reduction in sharpness following calibration, are also presented.

SEASON VARIATIONS OF ASTROCLIMATE PARAMETERS FOR THE TERSKOL OBSERVATORY

We present results of the study of seasonal variations of the astroclimate parameters for the Terskol Observatory: wind speed at the level of 200 mbar as a measure of the adaptive optics (AO) applicability, the wind speed altitude distribution, determining the requirements for the AO performance, moisture content to assess the possibility of AO operation in the IR range, the parameters of the mesospheric sodium layer, determining the brightness of the laser reference star for AO systems, in connection with the task of designing adaptive optics for the Zeiss-2000 telescope. Data on surface wind speed and total cloud cover are also analyzed to assess the available observation time. The data of atmospheric reanalysis were used, with the help of which the parameters under consideration have been studied in large astronomical observatories, as well as satellite data of measurements of mesospheric sodium and full-scale changes in surface wind velocity.

Изменения климатических условий на леднике Туйыксу

The article discusses the main meteorological elements of the average monthly: air temperature, relative humidity, total cloud cover from 0-3 (clear) and from 8-10 points (cloudy), wind speed, duration of sunshine, monthly precipitation according to the glaciological hospital of the Tuyiksu glacier for the period 1972-2022 in favorable and unfavorable years.

#2708 THE EFFECT OF PERCEIVED TEMPERATURE ON THE MORTALITY IN CHRONIC KIDNEY DISEASE PATIENTS

Abstract Background and Aims With the global warming, the interest in health risks from the high temperature exposure is growing. The perceived temperature is an equivalent temperature based on a complete heat budget model of the human body. We aimed to analyse the effect of perceived temperature on the overall mortality among patients with chronic kidney disease. Method A total of 32,870 patients with chronic kidney disease living in Seoul metropolitan region were recruited in a retrospective cohort (2001-2018). The perceived temperature during summer season (from July to September, at each year) was calculated using various climate factors including air temperature nearby automated weather station, dew point temperature, wind velocity, height of anemometer above ground, and total cloud amount. We assessed the association of perceived temperature using inverse distance weighting on mortality in patients with chronic kidney disease in the Cox proportional hazard model that was adjusted for sex, age, body mass index, estimated glomerular filtration rate, hypertension, and diabetes mellitus status. Results During the 6.14±3.96 years, 3,863 deaths (13%) were observed. We confirmed the significant effects of perceived temperature (average perceived temperature: hazard ratio [HR] 1.21, 95% confidence interval [CI] 1.18-1.23; minimum perceived temperature: HR 1.02, 95% CI 1.00-1.05; maximum perceived temperature: 1.20, 95% CI 1.18-1.22) on mortality among patients with chronic kidney disease in univariable analysis. In multivariable analysis, average perceived temperature (HR 1.22, 95% CI 1.19-1.25) and maximum perceived temperature (HR 1.20, 95% CI 1.17-1.23) showed increased risk for overall mortality among patients with chronic kidney disease. Conclusion Long-term exposure to high perceived temperature during summer season increased the risk of mortality among patients with chronic kidney disease.