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Results for “Journal of Climate and Applied Meteorology”

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At least 19 recordsLinked to original sources
USGS1984

The Palmer Drought Severity Index: limitations and assumptions.

The structure of the Palmer Drought Severity Index (PDSI), which is perhaps the most widely used regional index of drought, is examined. The PDSI addresses two of the most elusive properties of droughts: their intensity and their beginning and ending times. Under certain conditions, the PDSI values are very sensitive to the criteria for ending an 'established' drought and precipitation during a month can have a very large effect on the PDSI values for several previous months. -from Author

Journal of Climate and Applied Meteorology↗
USGS1985

Concentrations and source areas of ice nuclei in the Alaskan atmosphere.

The results indicate a seasonal variation in nucleus concentration with a winter minimum and a north-to-south trend in the increasing average concentration. Some episodes of high concentrations were correlated with 500 mb isobaric transport from Eurasia and 700 mb cyclogenesis over Alaska. These results suggest that local nucleus sources play a dominant role in the seasonal variation, while some individual episodes are caused by external or regional influences. -from Authors

Journal of Climate and Applied Meteorology↗
USGS1985

Streamflow variability in the United States: 1931-1978.

Systematic modes of spatial and temporal variation in a 48-year record of streamflow are defined using principal components. The components were calculated from a matrix of annual streamflow departures for 106 grid cells covering the United States in the years 1931-78. Five statistically significant components are found to account for more than 56% of the total variance. A varimax orthogonal rotation of the original components describes regional anomaly cores located in the middle Mississippi Valley, Pacific Northwest, Far West, Northeast, and northern Great Plains. -from Author

Journal of Climate and Applied Meteorology↗
USGS2017

Characterizing sources of uncertainty from global climate models and downscaling techniques

In recent years climate model experiments have been increasingly oriented towards providing information that can support local and regional adaptation to the expected impacts of anthropogenic climate change. This shift has magnified the importance of downscaling as a means to translate coarse-scale global climate model (GCM) output to a finer scale that more closely matches the scale of interest. Applying this technique, however, introduces a new source of uncertainty into any resulting climate model ensemble. Here we present a method, based on a previously established variance decomposition method, to partition and quantify the uncertainty in climate model ensembles that is attributable to downscaling. We apply the method to the Southeast U.S. using five downscaled datasets that represent both statistical and dynamical downscaling techniques. The combined ensemble is highly fragmented, in that only a small portion of the complete set of downscaled GCMs and emission scenarios are typically available. The results indicate that the uncertainty attributable to downscaling approaches ~20% for large areas of the Southeast U.S. for precipitation and ~30% for extreme heat days (> 35°C) in the Appalachian Mountains. However, attributable quantities are significantly lower for time periods when the full ensemble is considered but only a sub-sample of all models are available, suggesting that overconfidence could be a serious problem in studies that employ a single set of downscaled GCMs. We conclude with recommendations to advance the design of climate model experiments so that the uncertainty that accrues when downscaling is employed is more fully and systematically considered.

Journal of Applied Meteorology and Climatology↗
USGS2000

Coupled atmosphere-biophysics-hydrology models for environmental modeling

The formulation and implementation of LEAF-2, the Land Ecosystem–Atmosphere Feedback model, which comprises the representation of land–surface processes in the Regional Atmospheric Modeling System (RAMS), is described. LEAF-2 is a prognostic model for the temperature and water content of soil, snow cover, vegetation, and canopy air, and includes turbulent and radiative exchanges between these components and with the atmosphere. Subdivision of a RAMS surface grid cell into multiple areas of distinct land-use types is allowed, with each subgrid area, or patch, containing its own LEAF-2 model, and each patch interacts with the overlying atmospheric column with a weight proportional to its fractional area in the grid cell. A description is also given of TOPMODEL, a land hydrology model that represents surface and subsurface downslope lateral transport of groundwater. Details of the incorporation of a modified form of TOPMODEL into LEAF-2 are presented. Sensitivity tests of the coupled system are presented that demonstrate the potential importance of the patch representation and of lateral water transport in idealized model simulations. Independent studies that have applied LEAF-2 and verified its performance against observational data are cited. Linkage of RAMS and TOPMODEL through LEAF-2 creates a modeling system that can be used to explore the coupled atmosphere–biophysical–hydrologic response to altered climate forcing at local watershed and regional basin scales.

Journal of Applied Meteorology↗
USGS2015

Characterizing Congo Basin rainfall and climate using Tropical Rainfall Measuring Mission (TRMM) satellite data and limited rain gauge ground observations

Quantitative understanding of Congo River basin hydrological behavior is poor because of the basin’s limited hydrometeorological observation network. In cases such as the Congo basin where ground data are scarce, satellite-based estimates of rainfall, such as those from the joint NASA/JAXA Tropical Rainfall Measuring Mission (TRMM), can be used to quantify rainfall patterns. This study tests and reports the use of limited rainfall gauge data within the Democratic Republic of Congo (DRC) to recalibrate a TRMM science product (TRMM 3B42, version 6) in characterizing precipitation and climate in the Congo basin. Rainfall estimates from TRMM 3B42, version 6, are compared and adjusted using ground precipitation data from 12 DRC meteorological stations from 1998 to 2007. Adjustment is achieved on a monthly scale by using a regression-tree algorithm. The output is a new, basin-specific estimate of monthly and annual rainfall and climate types across the Congo basin. This new product and the latest version-7 TRMM 3B43 science product are validated by using an independent long-term dataset of historical isohyets. Standard errors of the estimate, root-mean-square errors, and regression coefficients r were slightly and uniformly better with the recalibration from this study when compared with the 3B43 product (mean monthly standard errors of 31 and 40 mm of precipitation and mean r 2 of 0.85 and 0.82, respectively), but the 3B43 product was slightly better in terms of bias estimation (1.02 and 1.00). Despite reasonable doubts that have been expressed in studies of other tropical regions, within the Congo basin the TRMM science product (3B43) performed in a manner that is comparable to the performance of the recalibrated product that is described in this study.

Journal of Applied Meteorology and Climatology↗
USGS1989

Velocities of antarctic outlet glaciers determined from sequential Landsat images

Approximately 91.0 percent of the volume of present-day glacier ice on Earth is in Antarctica; Greenland contains about another 8.3 percent of the volume. Thus, together, these two great ice sheets account for an estimated 99.3 percent of the total. Long-term changes in the volume of glacier ice on our planet are the result of global climate change. Because of the relationship of global ice volume to sea level (± 330 cubic kilometers of glacier ice equals ± 1 millimeter sea level), changes in the mass balance of the antarctic ice sheet are of particular importance. Whether the mass balance of the east and west antarctic ice sheets is positive or negative is not known. Estimates of mass input by total annual precipitation for the continent have been made from scattered meteorological observations (Swithinbank 1985). The magnitude of annual ablation of the ice sheet from calving of outlet glaciers and ice shelves is also not well known. Although the velocities of outlet glaciers can be determined from field measurements during the austral summer,the technique is costly, does not cover a complete annual cycle,and has been applied to just a few glaciers. To increase the number of outlet glaciers in Antarctica for which velocities have been determined and to provide additional data for under-standing the dynamics of the antarctic ice sheets and their response to global climate change, sequential Landsat image of several outlet glaciers were measured.

Antarctic Journal of the United States↗
USGS2006

Methodology and results of calculating central California surface temperature trends: Evidence of human-induced climate change?

A procedure is described to construct time series of regional surface temperatures and is then applied to interior central California stations to test the hypothesis that century-scale trend differences between irrigated and nonirrigated regions may be identified. The procedure requires documentation of every point in time at which a discontinuity in a station record may have occurred through (a) the examination of metadata forms (e.g., station moves) and (b) simple statistical tests. From this "homogeneous segments" of temperature records for each station are defined. Biases are determined for each segment relative to all others through a method employing mathematical graph theory. The debiased segments are then merged, forming a complete regional time series. Time series of daily maximum and minimum temperatures for stations in the irrigated San Joaquin Valley (Valley) and nearby nonirrigated Sierra Nevada (Sierra) were generated for 1910-2003. Results show that twentieth-century Valley minimum temperatures are warming at a highly significant rate in all seasons, being greatest in summer and fall (> +0.25??C decade-1). The Valley trend of annual mean temperatures is +0.07?? ?? 0.07??C decade-1. Sierra summer and fall minimum temperatures appear to be cooling, but at a less significant rate, while the trend of annual mean Sierra temperatures is an unremarkable -0.02?? ?? 0.10??C decade-1. A working hypothesis is that the relative positive trends in Valley minus Sierra minima (>0.4??C decade-1 for summer and fall) are related to the altered surface environment brought about by the growth of irrigated agriculture, essentially changing a high-albedo desert into a darker, moister, vegetated plain. ?? 2006 American Meteorological Society.

Journal of Climate↗
USGS2009

Detection and attribution of streamflow timing changes to climate change in the Western United States

This article applies formal detection and attribution techniques to investigate the nature of observed shifts in the timing of streamflow in the western United States. Previous studies have shown that the snow hydrology of the western United States has changed in the second half of the twentieth century. Such changes manifest themselves in the form of more rain and less snow, in reductions in the snow water contents, and in earlier snowmelt and associated advances in streamflow "center" timing (the day in the "water-year" on average when half the water-year flow at a point has passed). However, with one exception over a more limited domain, no other study has attempted to formally attribute these changes to anthropogenic increases of greenhouse gases in the atmosphere. Using the observations together with a set of global climate model simulations and a hydrologic model (applied to three major hydrological regions of the western United States_the California region, the upper Colorado River basin, and the Columbia River basin), it is found that the observed trends toward earlier "center" timing of snowmelt-driven streamflows in the western United States since 1950 are detectably different from natural variability (significant at the p < 0.05 level). Furthermore, the nonnatural parts of these changes can be attributed confidently to climate changes induced by anthropogenic greenhouse gases, aerosols, ozone, and land use. The signal from the Columbia dominates the analysis, and it is the only basin that showed a detectable signal when the analysis was performed on individual basins. It should be noted that although climate change is an important signal, other climatic processes have also contributed to the hydrologic variability of large basins in the western United States. ?? 2009 American Meteorological Society.

Journal of Climate↗
USGS2016

Climate change implications for tropical islands: Interpolating and interpreting statistically downscaled GCM projections for management and planning

The potential ecological and economic effects of climate change for tropical islands were studied using output from 12 statistically downscaled general circulation models (GCMs) taking Puerto Rico as a test case. Two model selection/model averaging strategies were used: the average of all available GCMs and the average of the models that are able to reproduce the observed large-scale dynamics that control precipitation over the Caribbean. Five island-wide and multidecadal averages of daily precipitation and temperature were estimated by way of a climatology-informed interpolation of the site-specific downscaled climate model output. Annual cooling degree-days (CDD) were calculated as a proxy index for air-conditioning energy demand, and two measures of annual no-rainfall days were used as drought indices. Holdridge life zone classification was used to map the possible ecological effects of climate change. Precipitation is predicted to decline in both model ensembles, but the decrease was more severe in the “regionally consistent” models. The precipitation declines cause gradual and linear increases in drought intensity and extremes. The warming from the 1960–90 period to the 2071–99 period was 4.6°–9°C depending on the global emission scenarios and location. This warming may cause increases in CDD, and consequently increasing energy demands. Life zones may shift from wetter to drier zones with the possibility of losing most, if not all, of the subtropical rain forests and extinction risks to rain forest specialists or obligates.

Puerto Rico↗
USGS2020

Climate change projected to reduce prescribed burning opportunities in the south-eastern United States

Prescribed burning is a critical tool for managing wildfire risks and meeting ecological objectives, but its safe and effective application requires that specific meteorological criteria (a ‘burn window’) are met. Here, we evaluate the potential impacts of projected climatic change on prescribed burning in the south-eastern United States by applying a set of burn window criteria that capture temperature, relative humidity and wind speed to projections from an ensemble of Global Climate Models under two greenhouse gas emission scenarios. Regionally, the percentage of suitable days for burning changes little during winter but decreases substantially in summer owing to rising temperatures by the end of the 21st century compared with historical conditions. Management implications of such changes for six representative land management units include seasonal shifts in burning opportunities from summer to cool-season months, but with considerable regional variation. We contend that the practical constraints of rising temperatures on prescribed fire activities represent a significant future challenge and show that even meeting basic burn criteria (as defined today) will become increasingly difficult over time, which speaks to the need for adaptive management strategies to prepare for such changes.

Alabama, Arkansas, Florida, Georgia, kentucky, Lou↗
USGS1992

Precipitation estimation in mountainous terrain using multivariate geostatistics. Part II: isohyetal maps

Values of average annual precipitation (AAP) may be important for hydrologic characterization of a potential high-level nuclear-waste repository site at Yucca Mountain, Nevada. Reliable measurements of AAP are sparse in the vicinity of Yucca Mountain, and estimates of AAP were needed for an isohyetal mapping over a 2600-square-mile watershed containing Yucca Mountain. Estimates were obtained with a multivariate geostatistical model developed using AAP and elevation data from a network of 42 precipitation stations in southern Nevada and southeastern California. An additional 1531 elevations were obtained to improve estimation accuracy. Isohyets representing estimates obtained using univariate geostatistics (kriging) defined a smooth and continuous surface. Isohyets representing estimates obtained using multivariate geostatistics (cokriging) defined an irregular surface that more accurately represented expected local orographic influences on AAP. Cokriging results included a maximum estimate within the study area of 335 mm at an elevation of 7400 ft, an average estimate of 157 mm for the study area, and an average estimate of 172 mm at eight locations in the vicinity of the potential repository site. Kriging estimates tended to be lower in comparison because the increased AAP expected for remote mountainous topography was not adequately represented by the available sample. Regression results between cokriging estimates and elevation were similar to regression results between measured AAP and elevation. The position of the cokriging 250-mm isohyet relative to the boundaries of pinyon pine and juniper woodlands provided indirect evidence of improved estimation accuracy because the cokriging result agreed well with investigations by others concerning the relationship between elevation, vegetation, and climate in the Great Basin. Calculated estimation variances were also mapped and compared to evaluate improvements in estimation accuracy. Cokriging estimation variances were reduced by an average of 54% relative to kriging variances within the study area. Cokriging reduced estimation variances at the potential repository site by 55% relative to kriging. The usefulness of an existing network of stations for measuring AAP within the study area was evaluated using cokriging variances, and twenty additional stations were located for the purpose of improving the accuracy of future isohyetal mappings. Using the expanded network of stations, the maximum cokriging estimation variance within the study area was reduced by 78% relative to the existing network, and the average estimation variance was reduced by 52%.

Nevada↗
USGS2013

Representing the effects of alpine grassland vegetation cover on the simulation of soil thermal dynamics by ecosystem models applied to the Qinghai-Tibetan Plateau

Soil surface temperature is a critical boundary condition for the simulation of soil temperature by environmental models. It is influenced by atmospheric and soil conditions and by vegetation cover. In sophisticated land surface models, it is simulated iteratively by solving surface energy budget equations. In ecosystem, permafrost, and hydrology models, the consideration of soil surface temperature is generally simple. In this study, we developed a methodology for representing the effects of vegetation cover and atmospheric factors on the estimation of soil surface temperature for alpine grassland ecosystems on the Qinghai-Tibetan Plateau. Our approach integrated measurements from meteorological stations with simulations from a sophisticated land surface model to develop an equation set for estimating soil surface temperature. After implementing this equation set into an ecosystem model and evaluating the performance of the ecosystem model in simulating soil temperature at different depths in the soil profile, we applied the model to simulate interactions among vegetation cover, freeze-thaw cycles, and soil erosion to demonstrate potential applications made possible through the implementation of the methodology developed in this study. Results showed that (1) to properly estimate daily soil surface temperature, algorithms should use air temperature, downward solar radiation, and vegetation cover as independent variables; (2) the equation set developed in this study performed better than soil surface temperature algorithms used in other models; and (3) the ecosystem model performed well in simulating soil temperature throughout the soil profile using the equation set developed in this study. Our application of the model indicates that the representation in ecosystem models of the effects of vegetation cover on the simulation of soil thermal dynamics has the potential to substantially improve our understanding of the vulnerability of alpine grassland ecosystems to changes in climate and grazing regimes.

Qinghai;Tibet↗
USGS2015

Assessing the vegetation condition impacts of the 2011 drought across the U.S. southern Great Plains using the vegetation drought response index (VegDRI)

The vegetation drought response index (VegDRI), which combines traditional climate- and satellite-based approaches for assessing vegetation conditions, offers new insights into assessing the impacts of drought from local to regional scales. In 2011, the U.S. southern Great Plains, which includes Texas, Oklahoma, and New Mexico, was plagued by moderate to extreme drought that was intensified by an extended period of record-breaking heat. The 2011 drought presented an ideal case study to evaluate the performance of VegDRI in characterizing developing drought conditions. Assessment of the spatiotemporal drought patterns represented in the VegDRI maps showed that the severity and patterns of the drought across the region corresponded well to the record warm temperatures and much-below-normal precipitation reported by the National Climatic Data Center and the sectoral drought impacts documented by the Drought Impact Reporter (DIR). VegDRI values and maps also showed the evolution of the drought signal before the Las Conchas Fire (the largest fire in New Mexico’s history). Reports in the DIR indicated that the 2011 drought had major adverse impacts on most rangeland and pastures in Texas and Oklahoma, resulting in total direct losses of more than $12 billion associated with crop, livestock, and timber production. These severe impacts on vegetation were depicted by the VegDRI at subcounty, state, and regional levels. This study indicates that the VegDRI maps can be used with traditional drought indicators and other in situ measures to help producers and government officials with various management decisions, such as justifying disaster assistance, assessing fire risk, and identifying locations to move livestock for grazing.

Journal of Applied Meteorology and Climatology↗
USGS2021

Remote sensing-based actual evapotranspiration assessment in a data-scarce area of Brazil: A case study of the Urucuia Aquifer System

The large groundwater reserves of the Urucuia Aquifer System (UAS) enabled agricultural development and economic growth in the western Bahia State, in northeastern Brazil. Over the last several years, concern has grown around the aquifer’s diminishing water levels, and water balance (WB) studies are in demand. Considering the lack of measured actual evapotranspiration (ET a ), a major component of the water cycle, this work uses the Operational Simplified Surface Energy Balance (SSEBop) model to estimate ET a , and compares it to basin-scale estimates from the Soil Moisture Accounting Procedure (SMAP) monthly model and from an annual WB closure method, based on gridded meteorological data and the Gravity Recovery and Climate Experiment (GRACE) product. Additionally, a comparative assessment of different versions of the SSEBop parameterization was performed. Moderate Resolution Imaging Spectroradiometer (MODIS) imagery was used to implement eight different versions of the SSEBop algorithm over the UAS between 2000 and 2013. SSEBop and SMAP ET a yielded similar seasonal patterns, with correlation coefficient (r) up to 0.65, mean difference (MD) of 0.8 mm/month and mean absolute difference (MAD) of 18.5 mm/month. Comparison of SSEBop annual ET a estimates to annual SMAP and WB closure estimates yielded low MD (12.1 and −7.3 mm/year, respectively) and MAD (82.5 and 82.8 mm/year, respectively), but also low r values (0.00 and 0.37, respectively). The comparison of the different SSEBop versions indicated the need to incorporate a calibration step of the aerodynamic heat resistance (r ah ) parameter. SSEBop results were also used for land cover and drought monitoring. Analysis indicates that agriculture, associated with an increasing trend of atmospheric evaporative demand, is responsible for the decrease in groundwater levels and streamflow in the studied time period.

Urucuia Aquifer System↗
USGS2010

Seasonal groundwater contribution to crop-water use assessed with lysimeter observations and model simulations

Groundwater evaporation can play an important role in crop-water use where the water table is shallow. Lysimeters are often used to quantify the groundwater evaporation contribution influenced by a broad range of environmental factors. However, it is difficult for such field facilities, which are operated under limited conditions within limited time, to capture the whole spectrum of capillary upflow with regard to the inter-seasonal variability of climate, especially rainfall. Therefore, in this work, the method of combining lysimeter and numerical experiments was implemented to investigate seasonal groundwater contribution to crop-water use. Groundwater evaporation experiments were conducted through a weighing lysimeter at an agricultural experiment station located within an irrigation district in the lower Yellow River Basin for two winter wheat growth seasons. A HYDRUS-1D model was first calibrated and validated with weighing lysimeter data, and then was employed to perform scenario simulations of groundwater evaporation under different depths to water table (DTW) and water input (rainfall plus irrigation) driven by long term meteorological data. The scenario simulations revealed that the seasonally averaged groundwater evaporation amount was linearly correlated to water input for different values of DTW. The linear regression could explain more than 70% of the variability. The seasonally averaged ratio of the groundwater contribution to crop-water use varied with the seasonal water input and DTW. The ratio reached as high as 75% in the case of DTW=1.0. m and no irrigation, and as low as 3% in the case of DTW=3.0. m and three irrigation applications. The results also revealed that the ratio of seasonal groundwater evaporation to potential evapotranspiration could be fitted to an exponential function of the DTW that may be applied to estimate seasonal groundwater evaporation. In this case study of multilayered soil profile, the depth at which groundwater may evaporate at potential rate was 0.60-0.65. m, and the extinction depth of groundwater evaporation was approximately 3.8. m. ?? 2010 Elsevier B.V.

Journal of Hydrology↗
USGS2023

Developing a stochastic hydrological model for informing lake water level drawdown management

Winter drawdown (WD) is a common lake management tool for multiple purposes such as flood control, aquatic vegetation reduction, and lake infrastructure maintenance. To minimize adverse impacts to a lake’s ecosystem, regulatory agencies may provide managers with general guidelines for drawdown and refill timing, drawdown magnitude, and outflow limitations. However, there is significant uncertainty associated with the potential to meet management targets due to variability in lake characteristics and hydrometeorology of each lake’s basin, making the use of modeling tools a necessity. In this context, we developed a hydrological modeling framework for lake water level drawdown management (HMF-Lake) and evaluated it at 15 Massachusetts lakes where WDs have been applied over multiple years for vegetation control. HMF-Lake is based on the daily lake water balance, with inflows simulated by a lumped rainfall-runoff model (Cemaneige-GR4J) and outflow rate calculated by a modified Target Storage and Release Based Method (TSRB). The model showed a satisfactory performance of simulating historical water levels (0.53 ≤ NSE ≤ 0.86), however, uncertainties from meteorological inputs and TSRB determined lake outflow rate affected the result accuracy. To account for these uncertainties, the model was executed stochastically to assess the ability of study lakes to follow the Massachusetts’ general WD guidelines: drawdown by Dec 1 and fully refilled by Apr 1. By using the stochastic HMF-Lake, the probabilities of each lake to reach the drawdown level by Dec 1 were calculated for different drawdown magnitudes (1–6 ft). The probability results suggest it was generally less possible for most of study lakes to achieve a drawdown of 3 ft or more by Dec 1. Moreover, we employed the stochastic model to derive the annual latest refill starting dates that ensure a 95 % probability of reaching the normal water level by Apr 1. We found starting a refill in March for drawdowns up to 6 ft was feasible for most of study lakes. These results provide lake managers with a quantitative understanding of the lake’s ability to follow the state guidelines. The model may be used to systematically evaluate current WD management strategies at state or regional scales and support adaptive WD management under changing climates.

Massachusetts↗
USGS2017

Examining the value of global seasonal reference evapotranspiration forecasts to support FEWS NET’s food insecurity outlooks

The Famine Early Warning Systems Network (FEWS NET) team provides food insecurity outlooks for several developing countries in Africa, Central Asia, and Central America. This study describes development of a new global reference evapotranspiration (ETo) seasonal reforecast and skill evaluation with a particular emphasis on the potential use of this dataset by the FEWS NET to support food insecurity early warning. The ETo reforecasts span the 1982-2009 period and are calculated following ASCE’s formulation of Penman-Monteith method driven by seasonal climate forecasts of monthly mean temperature, humidity, wind speed, and solar radiation from NCEP’s CFSv2 and NASA’s GEOS-5 models. The skill evaluation using deterministic and probabilistic scores, focuses on the December-February (DJF), March-May (MAM), June-August (JJA) and September-November (SON) seasons. The results indicate that ETo forecasts are a promising tool for early warning of drought and food insecurity. Globally, the regions where forecasts are most skillful (correlation >0.35 at lead-2) include Western U.S., northern parts of South America, parts of Sahel region and Southern Africa. The FEWS NET regions where forecasts are most skillful (correlation >0.35 at lead-3) include Northern Sub-Saharan Africa (DJF, dry season), Central America (DJF, dry season), parts of East Africa (JJA, wet Season), Southern Africa (JJA, dry season), and Central Asia (MAM, wet season). A case study over parts of East Africa for the JJA season shows that ETo forecasts in combination with the precipitation forecasts could have provided early warning of recent severe drought events (e.g., 2002, 2004, 2009) that contributed to substantial food insecurity in the region.

Journal of Applied Meteorology and Climatology↗